Results 41 to 50 of about 250,191 (314)
FocusedDropout for Convolutional Neural Network
CoRR, 2021 In convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially. Except randomly discarding regions or channels, many approaches try to overcome this defect by dropping influential units.
Tianshu Xie +5 more
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Interpretable Convolutional Neural Networks [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 This paper proposes a method to modify traditional convolutional neural networks (CNNs) into interpretable CNNs, in order to clarify knowledge representations in high conv-layers of CNNs. In an interpretable CNN, each filter in a high conv-layer represents a certain object part.
Quanshi Zhang +2 more
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Jurnal Teknologi Informasi dan Ilmu Komputer, 2021 Hadis merupakan sumber hukum dan pedoman kedua bagi umat Islam setelah Al-Qur’an dan banyak sekali hadis yang telah diriwayatkan oleh para ahli hadis selama ini.
Muhammad Yuslan Abu Bakar +1 more
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Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms [PDF]
, 2019 This paper designs a hybridized deep learning framework that integrates the Convolutional Neural Network for pattern recognition with the Long Short-Term Memory Network for half-hourly global solar radiation (GSR) forecasting.
Deo, Ravinesh C. +3 more
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Deep Convolutional Neural Network Algorithm for Prediction of the Mechanical Properties of Friction Stir Welded Copper Joints from its Microstructures [PDF]
, 2021 Convolutional Neural Network (CNN) is a special type of Artificial Neural Network which takes input in the form of an image. Like Artificial Neural Network they consist of weights that are estimated during training, neurons (activation functions), and an
Asmita, Suman, Akshansh, Mishra
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Airborne Network Traffic Identification Method under Small Training Samples
Xibei Gongye Daxue Xuebao, 2020 Due to the high cost and difficulty of traffic data set acquisition and the high time sensitivity of traffic distribution, the machine learning-based traffic identification method is difficult to be applied in airborne network environment. Aiming at this
doaj +1 more source
Biomolecules, 2021 Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful method to
Kaisa Liimatainen +3 more
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Optimization design of binary VGG convolutional neural network accelerator
Dianzi Jishu Yingyong, 2021 Most of the existing researches on accelerators of binary convolutional neural networks based on FPGA are aimed at small-scale image input, while the applications mainly take large-scale convolutional neural networks such as YOLO and VGG as backbone ...
Zhang Xuxin +3 more
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Quantum convolutional neural networks [PDF]
Nature Physics, 2019 12 pages, 11 figures. v2: New application to optimizing quantum error correction codes, added sample complexity analysis, more details for experimental realizations, and other minor ...
Iris Cong +2 more
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Convolutional Graph Neural Networks
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 2019 Convolutional neural networks (CNNs) restrict the, otherwise arbitrary, linear operation of neural networks to be a convolution with a bank of learned filters. This makes them suitable for learning tasks based on data that exhibit the regular structure of time signals and images.
Fernando Gama +3 more
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