Results 31 to 40 of about 304,469 (259)

Semi-Supervised Multi-Channel Speaker Diarization With Cross-Channel Attention

2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2023
Most neural speaker diarization systems rely on sufficient manual training data labels, which are hard to collect under real-world scenarios. This paper proposes a semi-supervised speaker diarization system to utilize large-scale multi-channel training data by generating pseudo-labels for unlabeled data.
Shilong Wu, Jun Du 0002, Mao-Kui He, Shutong Niu, Hang Chen 0001, Haitao Tang, Chin-Hui Lee 0001   +6 more
openaire   +2 more sources

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.
Xiaotian Li, Zhihua Li, Huiyuan Yang, Geran Zhao, Lijun Yin 0001   +4 more
openaire   +2 more sources

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, Daming Shi, Meiqin Guo, Xiaochun Cheng   +3 more
doaj   +1 more source

A Study on the Super Resolution Combining Spatial Attention and Channel Attention

Applied Sciences, 2023
Existing CNN-based super resolution methods have low emphasis on high-frequency features, resulting in poor performance for contours and textures. To solve this problem, this paper proposes single image super resolution using an attention mechanism that ...
Dongwoo Lee, Kyeongseok Jang, Soo Young Cho, Seunghyun Lee, Kwangchul Son   +4 more
doaj   +1 more source

A learnable EEG channel selection method for MI-BCI using efficient channel attention

Frontiers in Neuroscience, 2023
IntroductionDuring electroencephalography (EEG)-based motor imagery-brain-computer interfaces (MI-BCIs) task, a large number of electrodes are commonly used, and consume much computational resources. Therefore, channel selection is crucial while ensuring
Lina Tong, Yihui Qian, Liang Peng, Chen Wang, Zeng-Guang Hou, Zeng-Guang Hou   +5 more
doaj   +1 more source

Dual Channel Attention Networks

Journal of Physics: Conference Series, 2020
Abstract Channel attention is currently widely used in Computer Vision. Most existing channel attention networks are proposed based on Squeeze-and-Excitation Networks (SE- Net),which can obtain excellent performance by designing complex structures, however, they also has more additional network parameters and higher floating point ...
Jingchen Bian, Yugui Liu
openaire   +1 more source

ASCU-Net: Attention Gate, Spatial and Channel Attention U-Net for Skin Lesion Segmentation

Diagnostics, 2021
Segmentation of skin lesions is a challenging task because of the wide range of skin lesion shapes, sizes, colors, and texture types. In the past few years, deep learning networks such as U-Net have been successfully applied to medical image segmentation
Xiaozhong Tong, Junyu Wei, Bei Sun, Shaojing Su, Zhen Zuo, Peng Wu   +5 more
doaj   +1 more source

Guidelines for Pediatric Radiotherapy Simulation: A Report From the Children's Oncology Group Radiation Oncology Discipline

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors.
Parham Alaei, Stephen Mihalcik, Sujith Baliga, Young Kwok, Dana Casey, Eric Ehler, Christiane Burton, John C. Breneman, Daphne A. Haas‐Kogan, Suzanne L. Wolden, Arnold C. Paulino, Nadia N. Laack, Natia Esiashvili, Sarah Milgrom, Christine Hill‐Kayser, Thomas J. Fitzgerald, John A. Kalapurakal, Chia‐Ho Hua   +17 more
wiley   +1 more source

Intelligent Detection of Tomato Ripening in Natural Environments Using YOLO-DGS

Sensors
To achieve accurate detection of tomato fruit maturity and enable automated harvesting in natural environments, this paper presents a more lightweight and efficient maturity detection algorithm, YOLO-DGS, addressing the challenges of subtle maturity ...
Mengyuan Zhao, Beibei Cui, Yuehao Yu, Xiaoyi Zhang, Jiaxin Xu, Fengzheng Shi, Liang Zhao   +6 more
doaj   +1 more source

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, Aditya Sole, Jon Yngve Hardeberg   +2 more
doaj   +1 more source