Results 11 to 20 of about 7,675,115 (371)
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2019 Recently, channel attention mechanism has demonstrated to offer great potential in improving the performance of deep convolutional neural networks (CNNs).
Qilong Wang +5 more
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V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation [PDF]
International Conference on 3D Vision, 2016 Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most approaches are only able to process 2D images while most medical data used ...
F. Milletarì +2 more
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Scientific Reports, 2021 Semantic categorization is a fundamental ability in language as well as in interaction with the environment. However, it is unclear what cognitive and neural basis generates this flexible and context dependent categorization of semantic information.
Atsushi Matsumoto +3 more
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Plenoxels: Radiance Fields without Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2021 We introduce Plenoxels (plenoptic voxels), a systemfor photorealistic view synthesis. Plenoxels represent a scene as a sparse 3D grid with spherical harmonics.
Alex Yu +5 more
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Communications Biology, 2022 Modelling based on fMRI data obtained during more than 100 different cognitive tasks reveals that representation and decoding are preserved across the cortex, cerebellum, and ...
Tomoya Nakai, Shinji Nishimoto
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Non-local Neural Networks [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017 Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family of building blocks for capturing long-range dependencies.
X. Wang +3 more
semanticscholar +1 more source
Thermodynamic Neural Network [PDF]
Entropy, 2020 A thermodynamically motivated neural network model is described that self-organizes to transport charge associated with internal and external potentials while in contact with a thermal reservoir. The model integrates techniques for rapid, large-scale, reversible, conservative equilibration of node states and slow, small-scale, irreversible, dissipative
openaire +7 more sources
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2015 State-of-the-art deep neural networks have achieved impressive results on many image classification tasks. However, these same architectures have been shown to be unstable to small, well sought, perturbations of the images. Despite the importance of this
Seyed-Mohsen Moosavi-Dezfooli +2 more
semanticscholar +1 more source
Scientific Reports, 2022 While information enriches daily life, it can also sometimes have a negative impact, depending on an individual’s mental state. We recorded electroencephalogram (EEG) signals from depressed and non-depressed individuals classified based on the Beck ...
Kohei Fuseda +5 more
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A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2020 A convolutional neural network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to computer vision and natural language processing, it attracted much
Zewen Li +4 more
semanticscholar +1 more source