Results 1 to 10 of about 122,369 (167)
Modeling Interval Timing by Recurrent Neural Nets [PDF]
Frontiers in Integrative Neuroscience, 2019 The purpose of this study was to take a new approach in showing how the central nervous system might encode time at the supra-second level using recurrent neural nets (RNNs).
Theodore Raphan +5 more
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FPGA Implementation of Neural Nets [PDF]
International Journal of Electronics and Telecommunications, 2023 The field programmable gate array (FPGA) is used to build an artificial neural network in hardware. Architecture for a digital system is devised to execute a feed-forward multilayer neural network.
B A Sujatha Kumari +2 more
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Current Biology, 2015 Although modern evolutionary biology has abandoned the use of 'lower' or 'higher' for animals, the quote of G.H. Parker captures quite well the current understanding of the nerve net as the evolutionarily oldest organization of the nervous system, the major organ system responsible for processing information and coordinating animal behaviour.
Hejnol, Andreas, Rentzsch, Fabian
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Bayesian error propagation for neural-net based parameter inference
The Open Journal of Astrophysics, 2022 Neural nets have become popular to accelerate parameter inferences, especially for the upcoming generation of galaxy surveys in cosmology. As neural nets are approximative by nature, a recurrent question has been how to propagate the neural net's ...
Daniela Grandón, Elena Sellentin
doaj +1 more source
Network anomaly detection using deep learning techniques
CAAI Transactions on Intelligence Technology, 2022 Convolutional neural networks (CNNs) are the specific architecture of feed‐forward artificial neural networks. It is the de‐facto standard for various operations in machine learning and computer vision.
Mohammad Kazim Hooshmand +1 more
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A Review on Explainability in Multimodal Deep Neural Nets
IEEE Access, 2021 Artificial Intelligence techniques powered by deep neural nets have achieved much success in several application domains, most significantly and notably in the Computer Vision applications and Natural Language Processing tasks.
Gargi Joshi +2 more
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INSM1, a Novel Biomarker for Detection of Neuroendocrine Neoplasms: Cytopathologists’ View
Diagnostics, 2021 Background: Insulinoma-associated protein 1 (INSM1) has been considered as a novel immunostain for neuroendocrine tumors (NETs) and is hypothesized to be more reliable than first-generation NET biomarkers, such as CGA (chromogranin A), SYP (synaptophysin)
Zahra Maleki +5 more
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Side channel attacks for architecture extraction of neural networks
CAAI Transactions on Intelligence Technology, 2021 Side channel attacks (SCAs) on neural networks (NNs) are particularly efficient for retrieving secret information from NNs. We differentiate multiple types of threat scenarios regarding what kind of information is available before the attack and its ...
Hervé Chabanne +3 more
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Deep Net Tree Structure for Balance of Capacity and Approximation Ability
Frontiers in Applied Mathematics and Statistics, 2019 Deep learning has been successfully used in various applications including image classification, natural language processing and game theory. The heart of deep learning is to adopt deep neural networks (deep nets for short) with certain structures to ...
Charles K. Chui +4 more
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Compressing fully connected layers of deep neural networks using permuted features
IET Computers & Digital Techniques, 2023 Modern deep neural networks typically have some fully connected layers at the final classification stages. These stages have large memory requirements that can be expensive on resource‐constrained embedded devices and also consume significant energy just
Dara Nagaraju, Nitin Chandrachoodan
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