Results 41 to 50 of about 5,349,001 (214)
Normalized Convolutional Neural Network
CoRR, 2020 We introduce a Normalized Convolutional Neural Layer, a novel approach to normalization in convolutional networks. Unlike conventional methods, this layer normalizes the rows of the im2col matrix during convolution, making it inherently adaptive to sliced inputs and better aligned with kernel structures. This distinctive approach differentiates it from
Dongsuk Kim +4 more
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Cloud-based video analytics using convolutional neural networks. [PDF]
, 2018 Object classification is a vital part of any video analytics system, which could aid in complex applications such as object monitoring and management.
Anjum, Ashiq +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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Convolutional Neural Networks: A Survey
Computers, 2023 Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of AI that have emerged as a powerful tool for various tasks including image recognition, speech recognition, natural language processing (NLP), and even in the field of ...
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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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Factorial Convolution Neural Networks
CoRR, 2021 In recent years, GoogleNet has garnered substantial attention as one of the base convolutional neural networks (CNNs) to extract visual features for object detection. However, it experiences challenges of contaminated deep features when concatenating elements with different properties.
Jaemo Sung, Eun-Sung Jung
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SC-PNN: Saliency Cascade Convolutional Neural Network for Pansharpening
, 2021 In many remote sensing tasks, different types of regions or targets differ in requirements for spectral and spatial quality. The discrepancy reveals that a uniform pansharpening strategy applying to the entire image may not fulfill the varying demands of
Zhang, Jue +3 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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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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Test-object recognition in thermal images [PDF]
Компьютерная оптика, 2019 The paper presents a comparative analysis of several methods for recognition of test-object position in a thermal image when setting and testing characteristics of thermal image channels in an automated mode.
Aleksandr Mingalev +4 more
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