Results 31 to 40 of about 290,361 (261)
Multi-Attention Bottleneck for Gated Convolutional Encoder-Decoder-Based Speech Enhancement
IEEE Access, 2023 Convolutional encoder-decoder (CED) has emerged as a powerful architecture, particularly in speech enhancement (SE), which aims to improve the intelligibility and quality and intelligibility of noise-contaminated speech.
Nasir Saleem +4 more
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2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), 2021 Visual attention has been extensively studied for learning fine-grained features in both facial expression recognition (FER) and Action Unit (AU) detection. A broad range of previous research has explored how to use attention modules to localize detailed facial parts (e,g.
Li, Xiaotian +4 more
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A Nested UNet Based on Multi-Scale Feature Extraction for Mixed Gaussian-Impulse Removal
Applied Sciences, 2023 Eliminating mixed noise from images is a challenging task because accurately describing the attenuation of noise distribution is difficult. However, most existing algorithms for mixed noise removal solely rely on the local information of the image and ...
Jielin Jiang +3 more
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Movement recognition via channel-activation-wise sEMG attention
Methods, 2023 ABSTRACTContextSurface electromyography (sEMG) signals contain rich information recorded from muscle movements and therefore reflect the user’s intention. sEMG has seen dominant applications in reha-bilitation, clinical diagnosis as well as human engineering, etc.
Jiaxuan Zhang +4 more
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Channel Distillation: Channel-Wise Attention for Knowledge Distillation
, 2020 Knowledge distillation is to transfer the knowledge from the data learned by the teacher network to the student network, so that the student has the advantage of less parameters and less calculations, and the accuracy is close to the teacher. In this paper, we propose a new distillation method, which contains two transfer distillation strategies and a ...
Zhou, Zaida +3 more
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Densely Residual Network with Dual Attention for Hyperspectral Reconstruction from RGB Images
Remote Sensing, 2022 In the last several years, deep learning has been introduced to recover a hyperspectral image (HSI) from a single RGB image and demonstrated good performance. In particular, attention mechanisms have further strengthened discriminative features, but most
Lixia Wang +2 more
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Facial Landmark Detection via Attention-Adaptive Deep Network
IEEE Access, 2019 Facial landmark detection is a key component of the face recognition pipeline as well as facial attribute analysis and face verification. Recently convolutional neural network-based face alignment methods have achieved significant improvement, but ...
Muhammad Sadiq +3 more
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EEG-Based Auditory Attention Detection via Frequency and Channel Neural Attention [PDF]
IEEE Transactions on Human-Machine Systems, 2022 10.1109/thms.2021.3125283 ; IEEE Transactions on Human-Machine ...
Siqi Cai +3 more
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LCAM: Low-Complexity Attention Module for Lightweight Face Recognition Networks
Mathematics, 2023 Inspired by the human visual system to concentrate on the important region of a scene, attention modules recalibrate the weights of either the channel features alone or along with spatial features to prioritize informative regions while suppressing ...
Seng Chun Hoo +3 more
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Applied Sciences, 2022 To solve the problem that small drones in the sky are easily confused with background objects and difficult to detect, according to the characteristics of irregular movement, small size, and changeable shape of drones, using a regional target recognition
Jianghao Cheng +5 more
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