• Artificial Intelligence
  • One approach focused on biological processes in the brain while the other focused on the application of neural networks to artificial intelligence. (wikipedia.org)
  • He is known for his work in the fields of quantum computing and artificial intelligence, particularly on how to reverse-engineer the mind by gradually replacing the biological brain with artificial components, such as quantum nano-bots, electrodes, or a neural lace. (wikipedia.org)
  • Florian Neukart holds a Ph.D. in quantum computing and artificial intelligence from the Transilvania University of Brasov, as well as a master's degree in information technology from the CAMPUS02 University of Applied Sciences in Graz, and a master's degree in computer science from the Joanneum University of Applied Sciences in Kapfenberg. (wikipedia.org)
  • He received a BSc in Computer Science from the University of Leeds, and earned his PhD in Artificial Intelligence from Leeds in 1995. (wikipedia.org)
  • Almost two decades after IBM's computer Deep Blue beat world chess champion Garry Kasparov in the 1997 match, the strongest Go programs using artificial intelligence techniques only reached about amateur 5-dan level, and still could not beat a professional Go player without handicaps. (wikipedia.org)
  • CAD is an interdisciplinary technology combining elements of artificial intelligence and computer vision with radiological and pathology image processing. (wikipedia.org)
  • Arthur Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term "Machine Learning" in 1959 while at IBM. (wikipedia.org)
  • algorithm
  • citation needed] A key trigger for renewed interest in neural networks and learning was Werbos's (1975) backpropagation algorithm that effectively solved the exclusive-or problem and more generally accelerated the training of multi-layer networks. (wikipedia.org)
  • Following the classical backpropagation rule, the strength of the interactions are learned from a training set of desired input-output relations, and the quantum network thus 'learns' an algorithm. (wikipedia.org)
  • The authors do not attempt to translate the structure of artificial neural network models into quantum theory, but propose an algorithm for a circuit-based quantum computer that simulates associative memory. (wikipedia.org)
  • The memory states (in Hopfield neural networks saved in the weights of the neural connections) are written into a superposition, and a Grover-like quantum search algorithm retrieves the memory state closest to a given input. (wikipedia.org)
  • AlphaGo uses a Monte Carlo tree search algorithm to find its moves based on knowledge previously "learned" by machine learning, specifically by an artificial neural network (a deep learning method) by extensive training, both from human and computer play. (wikipedia.org)
  • mechanisms
  • Mechanisms underlying lotal bursting as well as coordinationbetween different levels of a spinal CPG generating locomotionhave been investigated using computer simulations. (diva-portal.org)
  • A general aim is to understand disease mechanisms at the level of protein network biology. (wikipedia.org)
  • How can the ontogenetic development of behavior be related to neural mechanisms? (wikipedia.org)
  • In the cases where competing models are unavailable, or where only gross responses have been measured or quantified, a clearly formulated model can guide the scientist in designing experiments to probe biochemical mechanisms or network connectivity. (wikipedia.org)
  • He investigated the relaxation properties of some chemical systems and developed the singularity theory for transient processes of dynamical systems, developed the method of path summation for solving the chemical kinetics equations, developed a theory of dynamic limitation and asymptotology of chemical reaction networks which was applied to modeling of biological signalling networks and mechanisms of microRNA action on translation regulation. (wikipedia.org)
  • recurrent
  • CAP depth - for a feedforward neural network, the depth of the CAPs is that of the network and is the number of hidden layers plus one (as the output layer is also parameterized), but for recurrent neural networks, in which a signal may propagate through a layer more than once, the CAP depth is potentially unlimited. (wikipedia.org)
  • simulate
  • An advantage lies in the exponential storage capacity of memory states, however the question remains whether the model has significance regarding the initial purpose of Hopfield models as a demonstration of how simplified artificial neural networks can simulate features of the brain. (wikipedia.org)
  • IEEE Computer
  • He was named by the IEEE Computer Society as one of the leading experts in predictive analytics. (wikipedia.org)
  • IEEE Computer Society. (wikipedia.org)
  • In 2007, he received the W. Wallace McDowell Award, the highest technical honor awarded by the IEEE Computer Society, for his pioneering contributions to theory, technique, and practice of pattern recognition, computer vision, and biometric recognition systems. (wikipedia.org)
  • He has also received numerous other awards, including the Guggenheim Fellowship, Humboldt Research Award, IAPR Pierre Devijver Award, Fulbright Fellowship, IEEE Computer Society Technical Achievement award, IAPR King-Sun Fu Prize, and IEEE ICDM Research Contribution Award. (wikipedia.org)
  • In 1984 he received the Computer Pioneer Award from the IEEE Computer Society. (wikipedia.org)
  • 1995
  • The first ideas on quantum neural computation were published independently in 1995 by Ron Chrisley and Subhash Kak. (wikipedia.org)
  • inputs
  • The number of inputs to neural networks must be kept within manageable limits to escape from the curse of dimensionality. (igi-global.com)
  • Machine learning tasks are typically classified into two broad categories, depending on whether there is a learning "signal" or "feedback" available to a learning system: Supervised learning: The computer is presented with example inputs and their desired outputs, given by a "teacher", and the goal is to learn a general rule that maps inputs to outputs. (wikipedia.org)
  • radial
  • Nearest-Neighbor Rule (e.g. k-nearest neighbors) Minimum distance classifier Cascade Classifier Naive Bayesian Classifier Artificial Neural Network Radial basis function network (RBF) Support Vector Machine (SVM) Principle Component Analysis (PCA) If the detected structures have reached a certain threshold level, they are highlighted in the image for the radiologist. (wikipedia.org)
  • detection
  • The visual cortex for the movement detection, consist of two layered networks, called the primary visual cortex (V1), followed by the middle temporal area (MT), in which nonlinear functions will play important roles in the visual systems. (igi-global.com)
  • By the optimization of the asymmetric networks, movement detection Equations are derived. (igi-global.com)
  • Then, it was clarified that the even - odd nonlinearity combined asymmetric networks, has the ability of generating directional vector in the stimulus change detection or movement detection, while symmetric networks need the time memory to have the same ability. (igi-global.com)
  • Moreover, the chapter must mention a number of strategies of emergence detection, useful for researchers performing computer simulations of ANN behaviours. (igi-global.com)
  • Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images. (wikipedia.org)
  • Computer-aided detection (CADe) systems are usually confined to marking conspicuous structures and sections. (wikipedia.org)
  • example applications include email filtering, detection of network intruders or malicious insiders working towards a data breach, optical character recognition (OCR), learning to rank, and computer vision. (wikipedia.org)
  • neuron
  • The dynamics of a single neuron, which forms one unit of a large brain network, are therefore relatively simple. (frontiersin.org)
  • Linearity may occur in the basic elements of a neural circuit such as the response of a postsynaptic neuron, or as an emergent property of a combination of nonlinear subcircuits. (wikipedia.org)
  • simulations
  • Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. (frontiersin.org)
  • By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. (frontiersin.org)
  • methods
  • Among these strategies it is possible to quote the reduction of ANN models to continuous models, such as the neural field models or the neural mass models, the recourse to the methods of Network Theory and the employment of techniques borrowed by Statistical Physics, like the one based on the Renormalization Group. (igi-global.com)
  • Go is considered much more difficult for computers to win than other games such as chess, because its much larger branching factor makes it prohibitively difficult to use traditional AI methods such as alpha-beta pruning, tree traversal and heuristic search. (wikipedia.org)
  • The MCTS effectively takes tree search methods commonly seen in computer chess programs and randomizes them. (wikipedia.org)
  • brain
  • The design of brain-computer interface for the wheelchair for physically disabled people is presented. (hindawi.com)
  • There are two different approaches to QNN research, one exploiting quantum information processing to improve existing neural network models (sometimes also vice versa), and the other one searching for potential quantum effects in the brain. (wikipedia.org)
  • Kak discussed the similarity of the neural activation function with the quantum mechanical Eigenvalue equation, and later discussed the application of these ideas to the study of brain function and the limitations of this approach. (wikipedia.org)
  • The connectome is the map of neural connections within the brain. (wikipedia.org)
  • The complexities and vast amount of neural connections in the human brain has slowed the complete mapping of the human connectome. (wikipedia.org)
  • pattern recognition
  • Exploring the use of pattern recognition, pattern identification and machine learning to support active collaboration between the user and the computer (PhD thesis). (wikipedia.org)
  • He also received best paper awards from the IEEE Transactions on Neural Networks (1996) and the Pattern Recognition journal (1987, 1991, and 2005). (wikipedia.org)
  • approaches
  • This model paved the way for neural network research to split into two approaches. (wikipedia.org)
  • Neural approaches are necessarily very diverse, as is evident through the variety of questions asked, measuring techniques used, relationships explored, and model systems employed. (wikipedia.org)
  • However, by using a Deep Convolutional Neural Network designed for long-term predictions, Darkforest has been able to substantially improve the win rate for bots over more traditional Monte Carlo Tree Search based approaches. (wikipedia.org)
  • Combining these two approaches is difficult because search-based engines work much faster than neural networks, a problem which was solved in Darkfores2 by running the processes in parallel with frequent communication between the two. (wikipedia.org)
  • 1996
  • In 1996, Quine joined Apple Computer where he initially worked as lead software engineer on the Apple Media Tool. (wikipedia.org)
  • experiments
  • Since the technological implementation of a quantum computer is still in a premature stage, such quantum neural network models are mostly theoretical proposals that await their full implementation in physical experiments. (wikipedia.org)
  • This argument is supported by experiments in the auditory system, which show that neural responses to complex sounds, like social calls, can not be predicted by the knowledge gained from studying the responses due to pure tones (one of the non-natural stimuli favored by auditory neurophysiologists). (wikipedia.org)
  • proposes
  • This work proposes the clustering of neural network filters to avoid having to label training data and to reduce the number of filters needed by the enhancement system. (igi-global.com)
  • research
  • Neural network research slowed until computers achieved far greater processing power. (wikipedia.org)
  • Some contributions reverse the approach and try to exploit the insights from neural network research in order to obtain powerful applications for quantum computing, such as quantum algorithmic design supported by machine learning. (wikipedia.org)
  • According to DeepMind's David Silver, the AlphaGo research project was formed around 2014 to test how well a neural network using deep learning can compete at Go. (wikipedia.org)
  • scientists
  • Based on his Google Scholar profile, he has an h-index of 169, which is the second highest (after Herbert A. Simon) among computer scientists identified in a survey published by UCLA professor Jens Palsberg. (wikipedia.org)
  • scientist
  • Daniel Nicholas Quine (formerly known as Daniel Nicholas Crow) is a computer scientist, currently VP Engineering at AltSchool. (wikipedia.org)
  • finite
  • This work led to work on nerve networks and their link to finite automata. (wikipedia.org)
  • The universal approximation theorem concerns the capacity of feedforward neural networks with a single hidden layer of finite size to approximate continuous functions. (wikipedia.org)
  • architecture
  • Darkfmcts3 is the most advanced version of Darkforest, which combines Facebook's most advanced convolutional neural network architecture from Darkfores2 with a Monte Carlo tree search. (wikipedia.org)
  • nodes
  • They may also include latent variables organized layer-wise in deep generative models such as the nodes in Deep Belief Networks and Deep Boltzmann Machines. (wikipedia.org)
  • activity
  • Since 1943, the neuropshychologist Warren McCulloch and the mathematician Walter Pitts published the paper "A Logical Calculus of the Ideas Immanent in Nervous Activity" establishing the foundation of the neural networks. (igi-global.com)
  • As the water of a river, neural activity is constantly changing, never staying still. (wikipedia.org)
  • The connectome is the riverbed which both guides the neural activity while also being shaped by the water over time. (wikipedia.org)
  • Illustrating how thinking and neural activity alters the connectome adding to the difficulty of mapping the human connectome that is constantly changing. (wikipedia.org)
  • nerve
  • The rate of information processing in biological neural systems are constrained by the speed at which an action potential can propagate down a nerve fibre. (wikipedia.org)
  • data
  • The Artificial Neural Network (ANN) models gained a wide popularity owing to a number of claimed advantages such as biological plausibility, tolerance with respect to errors or noise in the input data, learning ability allowing an adaptability to environmental constraints. (igi-global.com)
  • The amount of data that large or small organizations register using computer systems is very high. (igi-global.com)
  • A novel framework is proposed in this study that uses a spiking neural network for learning spatio-temporal and spectro-temporal data called NeuCube. (researchgateway.ac.nz)
  • NeuCube uses DeSNN (Dynamic Evolving Spiking Neural Network) to classify the data and to send the commands to virtual Quadcopter to move. (researchgateway.ac.nz)
  • The first functional networks with many layers were published by Ivakhnenko and Lapa in 1965, becoming the Group Method of Data Handling. (wikipedia.org)
  • One important motivation for these investigations is the difficulty to train classical neural networks, especially in big data applications. (wikipedia.org)
  • Concepts
  • This chapter is demonstrating a practical design of an intelligent type of controller using higher order neural network (HONN) concepts, for the excitation control of a practical power generating system. (igi-global.com)
  • 1948
  • In 1948, Rochester moved to IBM where he designed the IBM 701, the first general purpose, mass-produced computer. (wikipedia.org)
  • systems
  • Presently the there are various growing topics in the field of computer and information technologies, face expression analysis is one of the important and rapidly growing area in image processing and biometric systems. (techrepublic.com)
  • Artificial neural networks (ANNs) or connectionist systems are computing systems inspired by the biological neural networks that constitute animal brains. (wikipedia.org)
  • Instead, neural networks copy human play by training the AI systems on images of successful moves, the AI can effectively learn how to interpret how the board looks, as many grandmasters do. (wikipedia.org)
  • single
  • In 500 games against other available Go programs, including Crazy Stone and Zen, AlphaGo running on a single computer won all but one. (wikipedia.org)
  • In a similar matchup, AlphaGo running on multiple computers won all 500 games played against other Go programs, and 77% of games played against AlphaGo running on a single computer. (wikipedia.org)
  • field
  • The main problems and solutions proposed in this field are discussed and a new approach is proposed based on ensemble of neural networks trained by local and global features. (igi-global.com)
  • The existing field of neural modeling may also expand into neuroethological terrain, due to its practical uses in robotics. (wikipedia.org)
  • vision
  • Unlike previous image datasets used in computer vision, ImageNet [ 1 ] offers a very comprehensive database of more than 1.2 million categorized natural images of 1000+ classes. (pubmedcentralcanada.ca)
  • Vision P6 DSP, with 4X the peak performance of the Vision P5 DSP for demanding image and computer vision applications. (wikipedia.org)
  • problem
  • The ease of modelling and use makes the neural networks good problem solving agents. (igi-global.com)
  • Similarly, a neural net that somehow had Chaitin's constant exactly embedded in its weight function would be able to solve the halting problem, though constructing such an infinitely precise neural net, even if you somehow know Chaitin's constant beforehand, is impossible under the laws of quantum mechanics. (wikipedia.org)