Results 311 to 320 of about 1,429,068 (340)
Some of the next articles are maybe not open access.
2017
The importance of the deep neural network lies in the fact that it opened the door to the complicated non-linear model and systematic approach for the hierarchical processing of knowledge.
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The importance of the deep neural network lies in the fact that it opened the door to the complicated non-linear model and systematic approach for the hierarchical processing of knowledge.
openaire +2 more sources
Image Style Transfer Using Convolutional Neural Networks
Computer Vision and Pattern Recognition, 2016Leon A. Gatys+2 more
semanticscholar +1 more source
2018
In Chapter 8, we looked at a traditional neural network (NN). One of the limitations of a traditional NN is that it is not translation invariant—that is, a cat image on the upper right-hand corner of an image would be treated differently from an image that has a cat in the center of the image.
openaire +2 more sources
In Chapter 8, we looked at a traditional neural network (NN). One of the limitations of a traditional NN is that it is not translation invariant—that is, a cat image on the upper right-hand corner of an image would be treated differently from an image that has a cat in the center of the image.
openaire +2 more sources
An overview of real‐world data sources for oncology and considerations for research
Ca-A Cancer Journal for Clinicians, 2022Lynne T Penberthy+2 more
exaly
Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks
IEEE Journal of Solid-State Circuits, 2016Yu-hsin Chen+3 more
semanticscholar +1 more source
Failing Forward: Stability of Transparent Electrodes Based on Metal Nanowire Networks
Advanced Materials, 2021Jeffrey C Grossman+2 more
exaly
Soft Materials by Design: Unconventional Polymer Networks Give Extreme Properties
Chemical Reviews, 2021Hyunwoo Yuk, Shaoting Lin, Xiaoyu Chen
exaly
Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review
Neural Computation, 2017Waseem Rawat, Zenghui Wang
semanticscholar +1 more source