Results 281 to 290 of about 250,191 (314)

PlantCTCIP: Chromatin Interaction Prediction Using Convolutional Neural Network and Transformer in Plants. [PDF]

Plant Biotechnol J
Wang Z, Zhou S, Guo Z, Ning Z, Cai J, Zhao R, Xie A, Li Q, Zhang J, Zhao Y, Li P, Si H, Yan J, Peng Y, Liu J.   +14 more
europepmc   +1 more source

Convolutional neural network models describe the encoding subspace of local circuits in auditory cortex. [PDF]

Nat Neurosci
Wingert JC, Parida S, Norman-Haignere SV, David SV.   +3 more
europepmc   +1 more source

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Factorized Convolutional Neural Networks

2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017
In this paper, we propose to factorize the convolutional layer to reduce its computation. The 3D convolution operation in a convolutional layer can be considered as performing spatial convolution in each channel and linear projection across channels simultaneously.
Wang, Min, Liu, Baoyuan, Foroosh, Hassan
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Attentiondrop for Convolutional Neural Networks

2019 IEEE International Conference on Multimedia and Expo (ICME), 2019
Dropout has been widely used in fully connected networks but becomes less effective for convolutional neural networks (CNNs), since the spatially correlated features still allow dropped information to flow through the network. To make dropout more practical for CNNs, structured dropout methods have been recently proposed by dropping regions with fixed ...
Zhihao Ouyang, Yan Feng, Zihao He, Tianbo Hao, Tao Dai 0001, Shu-Tao Xia   +5 more
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Denoising Convolutional Neural Network

2015 IEEE International Conference on Information and Automation, 2015
Convolutional Neural Network (CNN) is a kind of deep artificial neural network. CNN has kinds of merits, such as multidimensional data input, and fewer parameters. However, the network always has the problem of overfitting due to lots of connection in the full connection layer.
Qingyang Xu, Chengjin Zhang, Li Zhang 0043   +2 more
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Restricted Convolutional Neural Networks

Neural Processing Letters, 2018
In this paper, a new type of convolutional neural network is proposed which is inspired by cellular automata research. This model is referred to as “restricted convolutional neural network” and its characteristic is that the feature maps are not fully connected, i.e.
Mehran Mirkhan, Mohammad Reza Meybodi
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In vitro convolutional neural networks

Nature Machine Intelligence, 2022
© 2022 Springer Nature Limited. Published 11 July 2022. The author declares no competing interests.
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A-optimal convolutional neural network

Neural Computing and Applications, 2016
In this paper, we propose a novel data representation-classification model learning algorithm. The model is a convolutional neural network (CNN), and we learn its parameters to achieve A-optimality. The input multi-instance data are represented by a CNN model, and then classified by a linear classification model.
Zihong Yin, Dehui Kong, Guoxia Shao, Xinran Ning, Warren Jin 0001, Jingyan Wang   +5 more
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