Natural Language Processing
https://doi.org/10.1007/978-3-031-04420-5_9
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https://doi.org/10.1007/978-3-031-04420-5_9
A branch of computer science and AI called natural language processing is focused on how computers and human languages interact.In order for computers to interpret written and spoken human language without the use of computer-driven languag...
https://doi.org/10.20894/ijcoa.101.012.002.001
The recent times have seen unprecedented growth in research and development in the field of Artificial Intelligence and its allied fields, subfields, like Machine Learning, Deep Learning and Natural Language Processing. The new found excite...
https://doi.org/10.1109/icicv50876.2021.9388380
Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...
https://doi.org/10.1007/s10462-023-10562-9
In the past few years literature on computational civil engineering has concentrated primarily on artificial intelligence (Al) applications involving expert system technology. This article discusses a different Al approach involving neural ...
https://doi.org/10.1111/j.1467-8667.1990.tb00377.x
Neural Network is defined as the ability of a group to solve more problems than its individual members.The idea brings that a group of people can solve problems efficiently and offer greater insight and a better answer than any one individu...
https://doi.org/10.4018/978-1-59140-176-6
This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been co...
https://doi.org/10.1142/p487
Neural networks are parallel, distributed, adaptive information-processing systems that develop their functionality in response to exposure to information. This paper is a tutorial for researchers intending to use neural nets for medical de...
https://doi.org/10.1177/0272989x9601600409
After collecting a data base of fingerprint images, we design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs an estimate of the probability that the two images...
https://doi.org/10.1162/neco.1993.5.3.402
Abstract Neural network technologies have taken center stage owing to their powerful computing capability for supporting deep learning in artificial intelligence. However, conventional synaptic devices such as SRAM and DRAM are not satisfac...
https://doi.org/10.1088/1361-6463/aae223
New technologies in engineering, physics and biomedicine are demanding increasingly complex methods of digital signal processing. By presenting the latest research work the authors demonstrate how real-time recurrent neural networks (RNNs) ...
https://doi.org/10.1002/047084535x
Neural Networks for speech processing. Neural Networks in the acquisition of speech by machine. The nervous system - fantasy and reality. Processing of complex stimuli in the mammalian cochlear nucleus. On the possible role of auditory peri...
Receptive field calculus, Jan J. Koenderink visual reconstruction and data fusion, D. Suter visual perception of translational and rotational motion, Jim-Shih Liaw, Irwin K. King and Michael A. Arbib neural network for recovering observer m...
Part 1 Fundamentals: basics of neuroscience and artificial neuron models graphs algorithms. Part 2 Feedforward networks: perceptrons and LMS algorithm complexity of learning using feedforward networks adaptive structure networks. Part 3 Rec...
Representation learning in heterogeneous graphs aims to pursue a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This...
https://doi.org/10.1145/3292500.3330961
Artificial neural networks are made up of highly interconnected layers of simple ‘neuron-like’ nodes. The neurons act as nonlinear processing elements within the network. An attractive property of artificial neural networks is that, given t...
https://doi.org/10.1049/ip-d.1991.0036
This is a survey of neural network applications in the real-world scenario. It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of current and emerging trends in ANN applications research and ar...
https://doi.org/10.1016/j.heliyon.2018.e00938
PMC: 6260436
https://doi.org/10.1016/j.eswa.2009.10.012
Classification is one of the most active research and application areas of neural networks. The literature is vast and growing. This paper summarizes some of the most important developments in neural network classification research. Specifi...
https://doi.org/10.1109/5326.897072
https://doi.org/10.1016/s0045-7949(01)00039-6