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  • proceedings
  • Krawec, who has been building robots since 1999, is a research assistant and PhD student in Computer Science at the Stevens Institute of Technology in Hoboken, N.J. The work presented in his two-part series is based on a paper published in the proceedings of the 13th International Artificial Life Conference in 2012. (circuitcellar.com)
  • S. Joo, W. K. Moon, and H. C. Kim, "Computer-aidied diagnosis of solid breast nodules on ultrasound with digital image processing and artificial neural network," in Proceedings of the 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '04) , pp. 1397-1400, September 2004. (hindawi.com)
  • On condition monitoring of exhaust valves in marine diesel engines," in Proceedings of the 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP '99) , vol. 9, pp. 554-563, Madison, Wis, USA, August 1999. (hindawi.com)
  • Classification
  • S. G. Mougiakakou, I. Valavanis, K. S. Nikita, A. Nikita, and D. Kelekis, "Characterization of CT liver lesions based on texture features and a multiple neural network classification scheme," in Proceddings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society , pp. 1287-1290, September 2003. (hindawi.com)
  • Approach
  • A new approach for determining the coefficients of a complex-valued autoregressive (CAR) and complex-valued autoregressive moving average (CARMA) model coefficients using complex-valued neural network (CVNN) technique is discussed in this paper. (hindawi.com)
  • The work, led by Nikhil Gupta, associate professor of mechanical and aerospace engineering at NYU Tandon, with Ph.D. student Xianbo Xu and collaborators at 2-D graphene materials manufacturer GrapheneCa, is detailed in "Artificial Neural Network Approach to Predict the Elastic Modulus from Dynamic Mechanical Analysis Results," which will be featured on the inside cover of the journal Advanced Theory and Simulations . (phys.org)
  • Applying an artificial neural network approach to predict the properties of nanocomposites can help in developing an approach where modeling can guide the material and application development and reduce the cost over time," continued Gupta. (phys.org)
  • Xianbo Xu et al, Artificial Neural Network Approach to Predict the Elastic Modulus from Dynamic Mechanical Analysis Results, Advanced Theory and Simulations (2019). (phys.org)
  • Accordingly, this study proposes an artificial neural network (ANN) mechanism to overcome the difficulties of typical MLE approach in determining the change point of an attribute process. (hindawi.com)
  • Our proposed approach involves the integrated use of the artificial neural network (ANN) and the binomial cumulative probability. (hindawi.com)
  • counterpart
  • This evolving paradigm has gained much attention not only because there are situations where CVNNs are inevitably required or greatly effective than its counterpart, the real-valued neural network (RVNN), but because of its usefulness which is enshrined in the fundamental theorem of Algebra [ 25 - 27 ]. (hindawi.com)
  • optimization
  • During the last decade, there has been an increased interest in applying new emerging theoretical techniques such as fuzzy inference system (FIS) and artificial neural network (ANN) for optimization-related problems [ 17 - 20 ]. (hindawi.com)
  • I have used Lagrange multipliers to arrive at the optimization of neural networks. (1e.com)
  • Lu, T., Chen, X. and Zhou, S. (2010) Optimization for impact factors of dam deformation based on BP neural network model. (scirp.org)
  • Data
  • It will use the network.nn file as a neural network, and load data form data1_file and data2_file , which represents data vectors from positive and negative classes, and train it for 1000 epochs. (codeproject.com)
  • This paper develops a process whereby a high-dimensional clustering problem is solved using a neural network and a low-dimensional cluster diagram of the results is produced using the Mapper method from topological data analysis. (hindawi.com)
  • In contrast with so-called expert systems that incorporate a knowledge (data) base, artificial neural networks do not have a database. (infobarrel.com)
  • In supervised training a data set from the problem under consideration is used to train the network. (infobarrel.com)
  • A subset of the available data, typically 70% is used to train the network. (infobarrel.com)
  • 30% of the data are used to validate the network. (infobarrel.com)
  • Investigators at the NYU Tandon School of Engineering have designed a machine learning system employing artificial neural networks (ANN) capable of extrapolating from data derived from just one sample, thereby quickly formulating and providing analytics on theoretical graphene-enhanced advanced composites. (phys.org)
  • The gray level run length matrix (GLRLM) feature shows better results when the network was tested against unknown data. (hindawi.com)
  • Theory
  • M. A. Arbib, The Handbook of Brain Theory and Neural Networks , Massachusetts Institute of Technology, 2003. (hindawi.com)
  • The book can be used as a tool kit by readers interested in applying networks to specific problems, yet it also presents theory and references outlining the last ten years of MLP research. (worldcat.org)
  • diagnosis
  • Chang, C.L. and Chen, C.H. (2009) Applying decision tree and neural network to increase quality of dermatologic diagnosis. (scirp.org)
  • Here, based on the extracted features from the ultrasonic images, we employed an artificial neural network for the diagnosis of disease conditions in liver and finding of the best classifier that distinguishes between abnormal and normal conditions of the liver. (hindawi.com)
  • Applications
  • Finally, the console implementation is easier to use, you avoid a lot of mouse clicking in GUI applications, and may automate the process with batch files for choosing the right network topology, the best performance on the validation and test sets, and so on. (codeproject.com)
  • In recent times, the introduction of complex-valued neural networks (CVNNs) has widened the scope and applications of artificial neural network (ANN) [ 25 - 34 ]. (hindawi.com)
  • Artificial neural networks have been used in a wide variety of problem solving applications, and the field is widening as new applications are found. (infobarrel.com)
  • The following examples serve to illustrate the variety of actual or potential neural network applications. (infobarrel.com)
  • These are the most widely used neural networks, with applications as diverse as finance (forecasting), manufacturing (process control), and science (speech and image recognition). (worldcat.org)
  • Sequences
  • In the work described in the Nature paper, Cherry, who is the first author on the paper, demonstrated that a neural network made out of carefully designed DNA sequences could carry out prescribed chemical reactions to accurately identify "molecular handwriting. (eurekalert.org)
  • concepts
  • This article explores basic artificial neural network (ANN) concepts and outlines the ENN I'm using in this project. (circuitcellar.com)
  • The opening chapter sets the stage, presenting the basic concepts in a clear and objective way and tackling important-yet rarely addressed-questions related to the use of neural networks in practical situations. (mit.edu)
  • Humans
  • Similar to how electronic computers and smart phones have made humans more capable than a hundred years ago, artificial molecular machines could make all things made of molecules, perhaps including even paint and bandages, more capable and more responsive to the environment in the hundred years to come. (eurekalert.org)
  • These networks, just like humans, learn by example. (drexel.edu)
  • molecular
  • Conceptual illustration of a droplet containing an artificial neural network made of DNA that has been designed to recognize complex and noisy molecular information, represented as 'molecular handwriting. (eurekalert.org)
  • Given a particular example of molecular handwriting, the DNA neural network can classify it into up to nine categories, each representing one of the nine possible handwritten digits from 1 to 9. (eurekalert.org)
  • Learning
  • This network will be capable of growing and learning in real time as the robot operates. (circuitcellar.com)
  • Learning vector quantization neural networks improve accuracy of transcranial color-coded duplex sonography in detection of middle cerebral artery spasm-preliminary report," Neuroinformatics , vol. 6, no. 4, pp. 279-290, 2008. (hindawi.com)
  • Journal
  • Y. Li and Z. Chi, "MR brain image segmentation based on self-organizing map network," International Journal of Information Technology , vol. 11, no. 8, 2005. (hindawi.com)