Behavior neural networks computer. Medical search. Frequent questions

Fully recurrent neural networks (FRNN) connect the outputs of all neurons to the inputs of all neurons. (wikipedia.org)
This is the most general neural network topology because all other topologies can be represented by setting some connection weights to zero to simulate the lack of connections between those neurons. (wikipedia.org)
In order to describe how neurons in the brain might work, they modeled a simple neural network using electrical circuits. (stanford.edu)
In 1951, Marvin Minsky, a graduate student inspired by earlier neuroscience research indicating that the brain was composed of an electrical network of neurons firing with all-or-nothing pulses, attempted to computationally model the behavior of a rat. (kdnuggets.com)
The key point, she said, is that they can provide representations-that is, an overall mathematical view of how neurons assemble into circuits to drive cognition, memory, and behavior. (singularityhub.com)
A better understanding of the circuits of neurons involved in different behaviors could aid researchers trying to develop treatments and medicines for psychiatric and neurodegenerative diseases, whose early symptoms can manifest as subtle changes in behavior. (axios.com)
The information can be used to recreate the behavior in a lab, where at the same time researchers can measure the activity of neurons in the brain or silence them, and see the effect on behavior. (axios.com)
Recurrent neural networks (RNNs) make connections between neurons in a directed cycle. (biztechmagazine.com)
On the neural side, neuroscientists are now pairing automated behavioral tracking with technologies for recording large populations of neurons and for silencing specific neurons to study the neural basis of social encounters with a level of precision that has not previously been possible. (simonsfoundation.org)
Additionally, social behavior neuroscientists are beginning to employ analysis tools, historically used in cortical areas, that can consider hundreds to thousands of neurons recorded simultaneously, leading to a reevaluation of how social brain regions guide behavior. (simonsfoundation.org)
A neural network is a bunch of neurons interlinked together. (turing.com)
A neural network itself can have any number of layers with any number of neurons in it. (turing.com)

LSTM combined with convolutional neural networks (CNNs) improved automatic image captioning. (wikipedia.org)
Convolutional neural networks (CNNs) apply to speech to text, text to speech and language translation. (biztechmagazine.com)
The article goes on to describe the convolutional neural networks (CNNs) now used in computer vision applications and how they can be fooled. (arnoldit.com)

The term "recurrent neural network" is used to refer to the class of networks with an infinite impulse response, whereas "convolutional neural network" refers to the class of finite impulse response. (wikipedia.org)
1 ] developed a 3D convolutional neural network architecture for human behavior recognition. (hindawi.com)

Artificial neural networks (ANNs) have existed in computational neurobiology since the late 1950s, when psychologist Frank Rosenblatt created what's known as perceptrons . (biztechmagazine.com)

They found the behavior of female mice, which are often excluded from scientific studies because there is a notion that changes in their hormones influence their behavior, is more predictable than that of males. (axios.com)
Using this approach, researchers at MIT and MIT-IBM Watson AI Lab have found that directly mapping the features of the mammalian visual cortex onto deep neural networks creates AI systems that are more predictable in their behavior and more robust to adversarial perturbations. (arnoldit.com)
When implemented in safety critical environments, the behavior of neural networks has to remain predictable and reliable even when facing faults within the system. (uni-stuttgart.de)

Based on the advantages of the BP network algorithm, the recognition of basketball technical actions can be better realized. (hindawi.com)
The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM's Watson triumphed on Jeopardy over puny human brains, computer programs can be trained to play Atari games. (skillsoft.com)
M. F. Mø ller, ``A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning'', Neural Networks 6 , 525 (1993). (lu.se)
C. Peterson and E. Hartman, ``Explorations of the Mean Field Theory Learning Algorithm'', Neural Networks 2 , 475 (1989). (lu.se)

Think of deep neural networks (DNNs) as more complex ANNs. (biztechmagazine.com)
These systems are known as artificial neural networks (ANNs) or simulated neural networks (SNNs). (turing.com)

A computer built to mimic the brain's neural networks produces similar results to that of the best brain-simulation supercomputer software currently used for neural-signaling research, finds a new study published in the open-access journal Frontiers in Neuroscience . (phys.org)
Sacha J. van Albada et al, Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model, Frontiers in Neuroscience (2018). (phys.org)
In computer vision , one interesting method to protect deep learning systems against adversarial attacks is to apply findings in neuroscience to close the gap between neural networks and the mammalian vision system. (arnoldit.com)
In a paper published on the bioRxiv preprint server , the researchers introduce VOneNet, an architecture that combines current deep learning techniques with neuroscience-inspired neural networks. (arnoldit.com)
Despite our deeply social nature, our understanding of the neuroscience of social behaviors lags far behind that of other types of behavior. (simonsfoundation.org)

A recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. (wikipedia.org)
In contrast to the uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. (wikipedia.org)
Artificial neural network model & hidden layers in multilayer artificial neur. (slideshare.net)
2020) "An Autoencoder and Artificial Neural Network-based Method to Estimate Parity Status of Wild Mosquitoes from Near-infrared Spectra," PLOS ONE, vol. 15, no. 6, 1-16. (marquette.edu)

A neural network is a reflection of the human brain's behavior. (turing.com)

The brain has multiple… levels of organization," going from genes and molecules to cells that connect into circuits, which magically lead to cognition and behavior, he said. (singularityhub.com)
An ergonomic reliability model based on an improved backpropagation neural network (BPNN) and human cognition reliability (HCR) is proposed for predicting and evaluating operation flows according to medical equipment VDTs. (techscience.com)
The postdoc will be led and advised by researchers at the Institute for Logic, Language and Computation (ILLC), University of Amsterdam, and the Donders Institute for Brain, Cognition and Behavior, Radboud University. (lu.se)

The AI tools are 'really powerful because you are getting behavior quantification at the scale the brain works - at millisecond precision,' says Cory Miller, a neurobiologist at the University of California San Diego, who studies the neural mechanisms of behaviors in marmoset monkeys. (axios.com)
The researchers lament the tendency of AI scientists toward pursuing larger and larger neural networks without slowing down to consider the latest findings of brain mechanisms. (arnoldit.com)
Putting these two advances together gives us enormous power in uncovering the mechanisms that shape social interactions, arguably the most complex behaviors that animals produce," Murthy says. (simonsfoundation.org)

In 2009, a Connectionist Temporal Classification (CTC)-trained LSTM network was the first RNN to win pattern recognition contests when it won several competitions in connected handwriting recognition. (wikipedia.org)

This paper is based on BP neural network's basketball technique action recognition and experimental verification. (hindawi.com)
After this first step, methods to reliably detect these different faults are implemented and tested, followed by mitigation actions to reduce the impact the error has on the neural network's output. (uni-stuttgart.de)

Elman and Jordan networks are also known as "Simple recurrent networks" (SRN). (wikipedia.org)

If you can generate behavior computationally, then the machine will give you insight about how the brain actually does it,' says Datta, adding that the possibility is 'really exciting. (axios.com)

ANFIS has the advantages of employing expert knowledge from the fuzzy inference system and the learning capability of neural networks. (scirp.org)

T. Tollenaere, ``SuperSAB: Fast Adaptive Backpropagation with Good Scaling Properties'', Neural Networks 3 , 561 (1990). (lu.se)

In 1993, a neural history compressor system solved a "Very Deep Learning" task that required more than 1000 subsequent layers in an RNN unfolded in time. (wikipedia.org)
Title: Macworld Music and Sound Bible / Christopher Yavelow Publisher: IDG books, 1993 (probably out of print) Subjects: Computer sound processing. (faqs.org)

Tagging B Quark Events in Aleph with Neural Networks'', Proceedings of Workshop in Neural Networks: From Biology to High Energy Physics, June 1991, Elba, Italy , eds. (lu.se)
Proceedings of the Neural Networks and Expert Systems in Medicine and Healthcare Conference, 324-326 (2001), eds. (lu.se)

The aim is to advance our knowledge of neural processing in the brain, to include learning and disorders such as epilepsy and Alzheimer's disease. (phys.org)
The ability to run large-scale detailed neural networks quickly and at low power consumption will advance robotics research and facilitate studies on learning and brain disorders. (phys.org)
It is presently unclear which computer architecture is best suited to study whole-brain networks efficiently. (phys.org)
Developed over the past 15 years and based on the structure and function of the human brain, SpiNNaker-part of the Neuromorphic Computing Platform of the Human Brain Project-is a custom-built computer composed of half a million of simple computing elements controlled by its own software. (phys.org)
Since the early days of computers, scholars have argued that the subjective, phenomenal states that make up the life of the mind are intimately linked to the information expressed at that time by the brain. (scientificamerican.com)
Although we often talk about the brain as a biological computer, it runs on both electrical and chemical information. (singularityhub.com)
Incorporating molecular data into artificial neural networks could nudge AI closer to a biological brain, he argued. (singularityhub.com)
AI-enabled micro-measurements of animals running, hunting, preening and playing are unlocking troves of new data that scientists now want to use to simulate animals and test theories about behavior and the brain. (axios.com)
A primary function of the brain is to produce behavior and help animals move through the world - but there are questions about how that happens, with ramifications for medicine and efforts to create artificial general intelligence (AGI). (axios.com)
The body gives us a missing link between what the brain evolved to do and how it operates in the real world,' says Talmo Pereira, a fellow at the Salk Institute for Biological Sciences who uses machine learning to study animal behavior. (axios.com)
The idea is to compare the behavior of the fake mouse, which is based on a model of the brain-body relationship, to a real mouse. (axios.com)
Research in flies, birds, rodents and other animals has uncovered both specialized social brain regions and brainwide support of social behaviors. (simonsfoundation.org)
Social settings make it particularly difficult to quantitatively measure behavior with sufficient precision, and relevant brain regions have been difficult to access for experimental observation. (simonsfoundation.org)
Pick your favorite social brain region, pick your favorite behavior, and all of a sudden you're able to combine them in whatever way you want. (simonsfoundation.org)
It is a set of neural networks that tries to enact the workings of the human brain and learn from its experiences. (turing.com)
Designing low-power and flexible artificial neural devices with artificial neural networks is a promising avenue for creating brain-computer interfaces (BCIs). (bvsalud.org)

As a commonly used deep learning model in the field of action recognition, BP neural network has been widely used in various scenarios, such as signal processing or pattern recognition, the construction of expert systems, and the production of robots. (hindawi.com)
This paper defines the network group events from aspects of the nature of the incident and influence and establishes a neural network of pattern recognition model that is used to fit the model. (scirp.org)
The model can recognize the network group events through continuous three days' various topics growth rate. (scirp.org)
The training results of pattern recognition model show that the accuracy rate of the judgment of the Internet Group events and the non-network group events is 72.7% and 75% respectively. (scirp.org)
Using the model of infectious disease problem is the difference to the network group events topic (this will cause the transmission coefficient and the coefficient of change and cure) and the impact of derivative public opinion on the duration of the incident. (scirp.org)
Anomaly detection can be considered as a classification problem where it builds models of normal network behavior, which it uses to detect new patterns that significantly deviate from the model. (arxiv.org)
In this paper, we propose a real time collective anomaly detection model based on neural network learning and feature operating. (arxiv.org)
In the quest for better human-AI interaction, a team of researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have created a new tool called Bayes-TrEx that allows developers and users to gain transparency into their AI model. (mit.edu)
Bayes-TrEx can also help with understanding model behaviors in novel situations. (mit.edu)
Amazingly, only the contextual model-one based on GPT-3-was able to accurately predict neural activity when tested on a new dataset. (singularityhub.com)
This is pretty strong evidence that the neural network model was required in order for us to understand what the cerebellum is doing," said Fyshe. (singularityhub.com)
The VOneNet architecture works by swapping out the first few CNN layers for a neural network model based on primates' primary visual cortex. (arnoldit.com)
A neuron is the base of the neural network model. (turing.com)
Model expected behavior. (uni.edu)

Ironically, John von Neumann himself suggested the imitation of neural functions by using telegraph relays or vacuum tubes. (stanford.edu)

He explains Watson's famous victory on Jeopardy, and he looks at how computers play games, describing AlphaGo and Deep Blue, which beat reigning world champions at the strategy games of Go and chess. (skillsoft.com)
This] would not have been possible without deep neural networks. (singularityhub.com)
The tools - SLEAP , DeepLabCut , and others - rely on deep neural networks and computer vision techniques called pose estimation that identify the joints of a body (the left knee, right shoulder or tip of the tail) in an image or video and output them as coordinates in space. (axios.com)
Workplace Automation: What are Deep Neural Networks? (biztechmagazine.com)
Changing business dynamics through AI will depend largely upon the use of deep neural networks, an outgrowth of artificial neural networks. (biztechmagazine.com)
Artificial Neural Networks vs. Deep Neural Networks: What's the Difference? (biztechmagazine.com)
How Can Businesses Use Deep Neural Networks? (biztechmagazine.com)
Another field of work is explainable AI, which tries to develop tools and techniques for investigating the decisions of deep neural networks. (venturebeat.com)
The research team is determined to forge ahead and find more ways to beneficially incorporate biology into deep neural networks. (arnoldit.com)
It allows computer programs to recognize patterns and solve problems in the fields of machine learning, deep learning, and artificial intelligence. (turing.com)
Neural networks are subtypes of machine learning and form the core part of deep learning algorithms. (turing.com)
System design to allow prediction of workers' behaviors using computer vision and deep learning. (cdc.gov)
DLNLF-net: Denoised local and non-local deep features fusion network for malignancy characterization of hepatocellular carcinoma. (cdc.gov)

2020) "Using Smart Meters to Learn Water Customer Behavior," IEEE Transaction on Engineering Management, 1-13. (marquette.edu)

Intrusion detection for computer network systems becomes one of the most critical tasks for network administrators today. (arxiv.org)
Besides, anomaly detection in network security is aim to distinguish between illegal or malicious events and normal behavior of network systems. (arxiv.org)
To function, a combination of computer programming and algorithms , a remotely controlled manipulator, actuators , control systems -- action, processing and perception -- real-time sensors and an element of automation help to inform what a robot or robotic system does. (techtarget.com)
Pereira is using SLEAP, the tool he developed, to quantify the body language of museum-goers, to try to detect early changes in behavior related to ALS and to look at how genetic changes to plants affect their root systems. (axios.com)
These two AI technologies - Neural Networks and Expert Systems - provide the intelligence that the scheduling function requires in order to generate good schedules within the restrictions imposed by real-time problems. (calpoly.edu)
Incorporation of developed pose recognition system in robots may result in: Development of robust human robot interaction systems allowing robots to take decisions based on predicted human behavior. (cdc.gov)

Evolving means, just growing populations of neural networks in an evolutionary-inspired way, including topology and synaptic weights, which also works with recurrent neural networks. (dkriesel.com)

Thus the network can maintain a sort of state, allowing it to perform such tasks as sequence-prediction that are beyond the power of a standard multilayer perceptron. (wikipedia.org)
But in terms of prediction, these studies are focused on a single event or post, so this paper attempts to train a neural network that can predict a variety of network group events. (scirp.org)

As computers became more advanced in the 1950's, it was finally possible to simulate a hypothetical neural network. (stanford.edu)

MADALINE was the first neural network applied to a real world problem, using an adaptive filter that eliminates echoes on phone lines. (stanford.edu)
The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS. (calpoly.edu)

These neural networks work with the principles of matrix multiplication to identify patterns within an image. (turing.com)

Both classes of networks exhibit temporal dynamic behavior. (wikipedia.org)
The tools have yielded insights about how marmoset monkeys catch flying insects , the neural basis for different behaviors - fighting back or running away - mice exhibit when they are bullied, and more. (axios.com)

How to improve the competitive level of basketball has become the research focus of biomechanics, psychophysiology, sports medicine, and computer science. (hindawi.com)
In recent years, some scholars began to use the neural network for micro-blog research. (scirp.org)
Most of the cur- rent research on anomaly detection is based on the learning of normally and anomaly behaviors. (arxiv.org)
Despite the later success of the neural network, traditional von Neumann architecture took over the computing scene, and neural research was left behind. (stanford.edu)
His research group has identified about 50 of these short units of behavior and the sequences in which they tend to occur in order to identify and predict different behaviors. (axios.com)
The research within the group can roughly be divided into geometric computer vision, cognitive vision and medical image analysis. (lu.se)

Recurrent neural networks are theoretically Turing complete and can run arbitrary programs to process arbitrary sequences of inputs. (wikipedia.org)
Although the first computers were developed during World War II [1,2], what seemed to truly spark the field of AI was a question proposed by Alan Turing in 1950 [3]: can a machine imitate human intelligence? (kdnuggets.com)
In this paper, Turing, often referred to as the 'father of computer science', asks the following question, 'Can machines think? (ibm.com)
From there, he offers a test, now famously known as the 'Turing Test', where a human interrogator would try to distinguish between a computer and human text response. (ibm.com)

AI methods are increasingly being used to help scientists measure the behaviors of animals, a laborious task that typically involves researchers watching animals and tracking and annotating their movements. (axios.com)
Because FIT-positive patients have the highest prevalence of these neoplasias, they offer the best context for investigating the ability of computer-aided detection (CAD) to support their diagnosis, the researchers note. (medscape.com)

As artificial intelligence (AI) models are increasingly used in complex situations - approving or denying loans, helping doctors with medical diagnoses, assisting drivers on the road, or even taking complete control - humans still lack a holistic understanding of their capabilities and behaviors. (mit.edu)
The event will follow the same capture the flag format as last year, where teams will solve increasingly difficult challenges across numerous categories including networking, coding, cryptography, and web application hacking. (fdu.edu)
The human-computer interaction method of cognitive VDT operation has become increasingly common because operators must process large amounts of information. (techscience.com)
Neuroscientists continue to grapple with how constrained behavior should be, and how emerging technologies can provide increasingly precise quantitative documentation of increasingly unconstrained behavior. (simonsfoundation.org)

First, design a basketball technique action recognition method based on BP neural network, analyze basketball actions, collect relevant test data, and divide the methods of basketball action recognition. (hindawi.com)
It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. (ibm.com)
However, recent advances in tools for precisely monitoring behavior coupled with advances in neural imaging technologies and analysis methods are poised to revolutionize the field. (simonsfoundation.org)
On the behavior side, new methods that build on decades of progress in machine vision can track socially engaged animals' movements in an automated way and with greater precision than ever before. (simonsfoundation.org)
Social behavior is really becoming this playground, thanks to the convergence of all of these different types of methods that have become available recently," says Lindsay Willmore , a former doctoral student at Princeton who is now at DeepMind. (simonsfoundation.org)
Over the past five to 10 years, a wellspring of new methods for automated behavior tracking has made it easier to study natural social behaviors. (simonsfoundation.org)
These methods were first developed for solitary animals, and applying them to social behavior has been no easy feat. "It's a much harder problem than analyzing behavior of solitary animals," Anderson says. (simonsfoundation.org)

To do so, the most common computer vision network architectures are analyzed focusing on the impact the injected faults have on their performance. (uni-stuttgart.de)

M. G. Simoes and B. K. Bose, "Neural Network Based Estimation of Feedback Signals for Vector Controlled Induction Motor Drive," IEEE Transactions on Industry Applications, Vol. 31, No. 3, 1995, pp. 620-629. (scirp.org)

When viewing motion images, the computer captures the human body motion trajectory and motion trend in real time to determine the position and shape of human body parts, then through the computer analyze the technical characteristics of the action, and report the analysis results to the coach or athlete. (hindawi.com)
Their tool, called "RoCUS", inspired by Bayes-TrEx, uses additional adaptations to analyze robot-specific behaviors. (mit.edu)

We also intend to further predict the behavioral intent of the person using temporal data and recurrent models of neural network in our system. (cdc.gov)

Vision-based intelligent human action recognition is the most challenging direction in the field of computer vision in recent years. (hindawi.com)
The last time generative AI loomed this large, the breakthroughs were in computer vision, but now the leap forward is in natural language processing. (ibm.com)
These new approaches, fueled by advances in computer vision and machine learning, can quickly translate hours of raw video of behaving animals into streams of data ready for analysis, such as the precise position of an animal's head or legs, or even sequences or libraries of inferred behavioral 'motifs. (simonsfoundation.org)
They are similar to MLPs but are usually used for pattern or image recognition, and computer vision. (turing.com)
Generally, neural networks focusing on computer vision are susceptible to two distinct fault types: internal and external errors. (uni-stuttgart.de)

Among them, from the perspective of computer science, by extracting various parameters and action recognition in the training process of athletes and basketball players, it can improve the scientificity of daily basketball skill training. (hindawi.com)
While a number of definitions of artificial intelligence (AI) have surfaced over the last few decades, John McCarthy offers the following definition in this 2004 paper (link resides outside ibm.com), ' It is the science and engineering of making intelligent machines, especially intelligent computer programs. (ibm.com)
At its simplest form, artificial intelligence is a field, which combines computer science and robust datasets, to enable problem-solving. (ibm.com)
Robotics is a branch of engineering and computer science that involves the conception, design, manufacture and operation of robots . (techtarget.com)
S. E. Fahlman, ``An Empirical Study of Learning Speed in Back-propagation Networks'', Carnegie-Mellon Computer Science Rpt. (lu.se)

This was coupled with the fact that the early successes of some neural networks led to an exaggeration of the potential of neural networks, especially considering the practical technology at the time. (stanford.edu)

R. Jacobs, ``Increased Rates of Convergence Through Learning Rate Adaption'', Neural Networks 1 , 295 (1988). (lu.se)

In his seminal paper, "Computing Machinery and Intelligence," he formulated a game, called the imitation game, in which a human, a computer, and a (human) interrogator are in three different rooms. (kdnuggets.com)
Since its release, the AI and its successors have written extraordinary human-like poetry, essays, songs, and computer code , generating works that stump judges tasked with determining machine from human. (singularityhub.com)
2019) "A light weight smartphone based human activity recognition system with high accuracy," Journal of Network and Computer Applications, no. 141, 59-72. (marquette.edu)
For the adolescent, this issue becomes even more important, as it is a phase of human development in which the person exhibits behaviors of risk and during this stage of life there is a process of maturation of the central nervous system, which are related to decision-making and motivational processes. (bvsalud.org)

Therefore, this article mainly studies basketball actions based on BP neural network and validates the recognition method through basketball action experiments. (hindawi.com)
At the same time, they are still bad enough to make dumb mistakes, as these experiments by computer scientist Ernest Davis show. (venturebeat.com)
Neuroscientists design behavioral experiments balancing two needs: Behavior needs to be controlled enough to be quantitatively described and tied to relevant neural activity, but not so tightly controlled that it ceases to resemble 'normal' behavior. (simonsfoundation.org)

The various functional blocks of the system which govern the system behavior for small variations about the operating point are derived, and the transient responses are presented. (scirp.org)

In 1949, Donald Hebb wrote The Organization of Behavior , a work which pointed out the fact that neural pathways are strengthened each time they are used, a concept fundamentally essential to the ways in which humans learn. (stanford.edu)

Machine learning by using python lesson 2 Neural Networks By Professor Lili S. (slideshare.net)
Although quantum neural networks (QNNs) have shown promising results in solving simple machine learning tasks recently, for the time being, the effect of entanglement in QNNs and the behavior of QNNs in binary pattern classification are still underexplored. (ox.ac.uk)
Machine learning and neural theory pave new avenues in historically challenging terrain. (simonsfoundation.org)
How neural network models in Machine Learning work? (turing.com)

The second clinical trial of the BrainGate Neural Interface System developed at Brown University is about to start at Massachusetts General Hospital (MGH) in Boston. (acm.org)
Other possible solutions include multiple output suggestions, configuration sliders, and other tools that provide users with control over the behavior of the AI system they are using. (venturebeat.com)
This is one situation where the law, both statute and case law, create a "market" in which good behavior has value beyond a person's own belief system. (uni.edu)

In collaboration with physics graduate student Dean Edmonds, he built the first neural network machine called Stochastic Neural Analogy Reinforcement Computer (SNARC) [5]. (kdnuggets.com)

In our previous work, we use Hopfield Neural Network (HNN) to solve the energy function of the scheduling multi-processor tasks problem. (ijcsns.org)

Particle swarm optimization (PSO) is an evolutionary computation technique mimicking the behavior of flying birds and their means of information exchange. (ijcsns.org)

I want to add a nice chapter on evolving neural networks (which is, for example, one of the focuses of SNIPE, too). (dkriesel.com)
A program that focuses on the scientific study of the ecology and behavior of microbes, plants, and animals inhabiting oceans, coastal waters, and saltwater wetlands and their interactions with the physical environment. (myfuture.com)

Quantized neural networks typically require smaller memory footprints and lower computation complexity, which is crucial for efficient deployment. (icml.cc)

Animal behavior scientists, or ethologists, use the AI tools to track the natural behaviors of single - and more recently multiple - animals. (axios.com)

However, quantization inevitably leads to a distribution divergence from the original network, which generally degrades the performance. (icml.cc)

Anatomy14

Organisms3

Chemicals and Drugs2

Analytical, Diagnostic and Therapeutic Techniques and Equipment50

Psychiatry and Psychology57

Phenomena and Processes46

Disciplines and Occupations8

Anthropology, Education, Sociology and Social Phenomena11

Technology, Industry, Agriculture3

Humanities1

Information Science51

Health Care24

Geographicals1

Neurons12

CNNs3

Convolutional neural network2

Neurobiology1

Predictable3

Algorithm4

ANNS2

Neuroscience5

Artificial neural4

Brain's1

Cognition3

Mechanisms3

Handwriting recognition1

Network's2

Recurrent networks1

Computationally1

Inference1

Backpropagation1

19932

Proceedings2

Brain16

Model14

Suggested the imitation1

Deep13

20201

Systems6

Topology1

Prediction2

Simulate1

Adaptive2

Principles1

Exhibit2

Research6

Turing4

Researchers2

Increasingly4

Methods7

Architectures1

Estimation1

Analyze2

Temporal1

Vision5

Science5

Successes1

Convergence1

Human4

Experiments3

Functional1

Organization1

Machine Learning4

System3

Graduate1

Solve1

Birds1

Focuses2

Typically1

Scientists1

Generally1