Results 81 to 90 of about 9,085,112 (391)
A Comprehensive Review of Spiking Neural Networks: Interpretation, Optimization, Efficiency, and Best Practices [PDF]
arXiv, 2023 Biological neural networks continue to inspire breakthroughs in neural network performance. And yet, one key area of neural computation that has been under-appreciated and under-investigated is biologically plausible, energy-efficient spiking neural networks, whose potential is especially attractive for low-power, mobile, or otherwise hardware ...
arxiv
FEBS Letters, EarlyView.In lymphoid organs, antigen recognition and B cell receptor signaling rely on integrins and the cytoskeleton. Integrins act as mechanoreceptors, couple B cell receptor activation to cytoskeletal remodeling, and support immune synapse formation as well as antigen extraction.
Abhishek Pethe, Tanja Nicole Hartmann
wiley +1 more source
Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Prediction of battery charging process based on aggregation neural network
The Journal of Engineering, 2022 An online sequence extreme learning machine neural network prediction model based on sample aggregation method (AOSELM) is proposed, which is used to solve the prediction of the charging process of lead‐acid batteries.
Shuo Sun +4 more
doaj +1 more source
The neural network art which uses the Hamming distance to measure an image similarity score [PDF]
, 2019 This study reports a new discrete neural network of Adaptive Resonance Theory (ART-1H) in which the Hamming distance is used for the first time to estimate the measure of binary images (vectors) proximity.
Dmitrienko, V. D. +2 more
core
Molecular Oncology, EarlyView.Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever +1 more
wiley +1 more source
Using Burstiness for Network Applications Classification
Journal of Computer Networks and Communications, 2019 Network traffic classification is a vital task for service operators, network engineers, and security specialists to manage network traffic, design networks, and detect threats.
Hussein Oudah +4 more
doaj +1 more source
Graph Structure of Neural Networks [PDF]
arXiv, 2020 Neural networks are often represented as graphs of connections between neurons. However, despite their wide use, there is currently little understanding of the relationship between the graph structure of the neural network and its predictive performance.
arxiv
A VLSI Neural Network for Color Constancy [PDF]
, 1991 A system for color correction has been designed, built, and tested successfully; the essential components are three custom chips built using sub-threshold analog CMOS VLSI. The system, based on Land's Retinex theory of color constancy, produces colors
Allman, John +3 more
core +1 more source
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source