Results 31 to 40 of about 1,432,491 (277)

A Lightweight Convolutional Neural Network Based on Group-Wise Hybrid Attention for Remote Sensing Scene Classification

Remote Sensing, 2021
With the development of computer vision, attention mechanisms have been widely studied. Although the introduction of an attention module into a network model can help to improve classification performance on remote sensing scene images, the direct ...
Cuiping Shi, Xinlei Zhang, Jingwei Sun, Liguo Wang   +3 more
doaj   +1 more source

Dual-Branch Attention-In-Attention Transformer for Single-Channel Speech Enhancement

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022
Curriculum learning begins to thrive in the speech enhancement area, which decouples the original spectrum estimation task into multiple easier sub-tasks to achieve better performance. Motivated by that, we propose a dual-branch attention-in-attention transformer dubbed DB-AIAT to handle both coarse- and fine-grained regions of the spectrum in parallel.
Yu, Guochen, Li, Andong, Zheng, Chengshi, Guo, Yinuo, Wang, Yutian, Wang, Hui   +5 more
openaire   +2 more sources

Channel Attention Networks for Robust MR Fingerprint Matching

IEEE Transactions on Biomedical Engineering, 2022
Magnetic Resonance Fingerprinting (MRF) enables simultaneous mapping of multiple tissue parameters such as T1 and T2 relaxation times. The working principle of MRF relies on varying acquisition parameters pseudo-randomly, so that each tissue generates its unique signal evolution during scanning.
Refik Soyak, Ebru Navruz, Eda Ozgu Ersoy, Gastao Cruz, Claudia Prieto, Andrew P. King, Devrim Unay, Ilkay Oksuz   +7 more
openaire   +5 more sources

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, Teddy Surya Gunawan, Muhammad Shafi, Sami Bourouis, Aymen Trigui   +4 more
doaj   +1 more source

Your “Attention” Deserves Attention: A Self-Diversified Multi-Channel Attention for Facial Action Analysis

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, Li, Zhihua, Yang, Huiyuan, Zhao, Geran, Yin, Lijun   +4 more
openaire   +2 more sources

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, Li Liu, Yan Cui, Yingnan Zhao   +3 more
doaj   +1 more source

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, Yuki Matsuda, Manato Fujimoto, Hirohiko Suwa, Keiichi Yasumoto   +4 more
openaire   +2 more sources

Unitarity Meets Channel-Duality for Rolling / Decaying D-Branes [PDF]

, 2006
Investigations for decay of unstable D-brane and rolling of accelerated D-brane dynamics have revealed that various proposed prescriptions give different result for spectral amplitudes and observables.
A. Maloney, A. Sen, A. Sen, A. Strominger, A. Strominger, A.B. Zamolodchikov, B. Chen, B. Craps, B. Durin, B. Pioline, C. Bachas, chapter 6 of C. Itzykson, D. Bak, D. Kutasov, D. Kutasov, D.A. Sahakyan, H. Liu, H. Liu, I.R. Klebanov, J. Simon, J.L. Karczmarek, K. Okuyama, K. Okuyama, M. Berkooz, M. Gutperle, N. Lambert, R.C. Myers, S. Elitzur, S. Ribault, S.J. Rey, S.J. Rey, Soo-Jong Rey, T. Eguchi, T.G. Erler, V. Fateev, V. Schomerus, Y. Hikida, Y. Nakayama, Y. Nakayama, Y. Nakayama, Y.I. Kogan, Yu Nakayama, Yuji Sugawara   +42 more
core   +3 more sources

Channel estimation and transmit power control in wireless body area networks [PDF]

, 2014
Wireless body area networks have recently received much attention because of their application to assisted living and remote patient monitoring. For these applications, energy minimisation is a critical issue since, in many cases, batteries cannot be ...
Atkinson, Robert C., Di Francco, Fabio, Glover, Ian, Tachtazis, Christos, Tinnirello, Ilenia   +4 more
core   +2 more sources

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, Zhuge, Chaoran, Guan, Xinwei, Liu, Wen   +3 more
openaire   +2 more sources