Results 11 to 20 of about 4,718,784 (295)
WaveNets: Wavelet Channel Attention Networks [PDF]
2022 IEEE International Conference on Big Data (Big Data), 2022 IEEE BigData2022 ...
Hadi Salman +3 more
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Channel Attention Networks for Image Translation [PDF]
IEEE Access, 2019 Existing image-to-image translation methods usually adopt an encoder-decoder structure to generate images. The encoder extracts the features of input images using a sequence of convolution layers until a bottleneck, and then, the intermediate features ...
Song Sun +4 more
doaj +2 more sources
Proceedings of the AAAI Conference on Artificial Intelligence, 2022 Spatial and channel attentions, modelling the semantic interdependencies in spatial and channel dimensions respectively, have recently been widely used for semantic segmentation. However, computing spatial and channel attentions separately sometimes causes errors, especially for those difficult cases.
Ye Huang +4 more
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MCA: Moment Channel Attention Networks [PDF]
Proceedings of the AAAI Conference on Artificial IntelligenceChannel attention mechanisms endeavor to recalibrate channel weights to enhance representation abilities of networks. However, mainstream methods often rely solely on global average pooling as the feature squeezer, which significantly limits the overall potential of models.
Yangbo Jiang +4 more
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PKCAM: Previous Knowledge Channel Attention Module [PDF]
CoRR, 2022 Recently, attention mechanisms have been explored with ConvNets, both across the spatial and channel dimensions. However, from our knowledge, all the existing methods devote the attention modules to capture local interactions from a uni-scale. In this paper, we propose a Previous Knowledge Channel Attention Module(PKCAM), that captures channel-wise ...
Eslam Mohamed Bakr +2 more
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Automatic Channel Pruning for Multi-Head Attention [PDF]
CoRRDespite the strong performance of Transformers, their quadratic computation complexity presents challenges in applying them to vision tasks. Automatic pruning is one of effective methods for reducing computation complexity without heuristic approaches.
Eunho Lee, Youngbae Hwang
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Auditory attention detection with EEG channel attention [PDF]
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021 Abstract Auditory attention detection (AAD) seeks to detect the attended speech from EEG signals in a multi-talker scenario, i.e. cocktail party. As the EEG channels reflect the activities of different brain areas, a task-oriented channel selection technique improves the performance of brain-computer interface applications.
Enze Su +4 more
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Attention: A view suggested by systemic and cybernetic consideration [PDF]
, 1978 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Current views and models about attention regard man as a 'transmitter channel' and try to characterise the properties of that 'odd channel'.
Hernandez-Chavez, Francisco Jose
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3D CATBraTS: Channel Attention Transformer for Brain Tumour Semantic Segmentation [PDF]
, 2023 Brain tumour diagnosis is a challenging task yet crucial for planning treatments to stop or slow the growth of a tumour. In the last decade, there has been a dramatic increase in the use of convolutional neural networks (CNN) for their high performance ...
Bonmati Coll, E. +3 more
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OrthoNets: Orthogonal Channel Attention Networks
2023 IEEE International Conference on Big Data (BigData), 2023 IEEE BigData ...
Hadi Salman +3 more
openaire +3 more sources