Results 31 to 40 of about 4,485,063 (290)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Target detection is a critical task in interpreting aerial images. Small target detection, such as vehicles, is challenging. Different lighting conditions affect the accuracy of vehicle detection.
Yuanfeng Wu +4 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.
Guochen Yu +5 more
openaire +4 more sources
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 +3 more
doaj +1 more source
Telephone conversation impairs sustained visual attention via a central bottleneck [PDF]
, 2008 Recent research has shown that holding telephone conversations disrupts one's driving ability. We asked whether this effect could be attributed to a visual attention impairment.
Randall Carter +7 more
core +2 more sources
Channel attention module structure.
, 2022 Channel attention module structure.
Mengmeng Chen (565957) +2 more
core +1 more source
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
doaj +1 more source
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
doaj +1 more source
The control of attention to faces [PDF]
, 2007 Humans attend to faces. This study examines the extent to which attention biases to faces are under top-down control. In a visual cueing paradigm, observers responded faster to a target probe appearing in the location of a face cue than of a competing ...
Schweinberger, S +18 more
core +1 more source
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 +6 more
openaire +3 more sources
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 +4 more
openaire +3 more sources