Densely convolutional attention network for image super-resolution
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.08.070
Abstract: Abstract Recently, deep convolutional neural networks (CNNs) with skip-connections in single image super-resolution (SISR) have received great success. However, the difficulty of reconstructing high-resolution images is particularly pronounced for the limited information extracted from input… read more here.
Keywords: resolution; network; convolutional attention; super resolution ... See more keywords
Continuous Estimation of Human Joint Angles From sEMG Using a Multi-Feature Temporal Convolutional Attention-Based Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3198640
Abstract: Intention recognition based on surface electromyography (sEMG) signals is pivotal in human-machine interaction (HMI), where continuous motion estimation with high accuracy has been the challenge. The convolutional neural network (CNN) possesses excellent feature extraction capability.… read more here.
Keywords: convolutional attention; network; feature temporal; temporal convolutional ... See more keywords
Hierarchical Convolutional Attention Network for Depression Detection on Social Media and Its Impact During Pandemic.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2023.3243249
Abstract: People across the globe have felt and are still going through the impact of COVID-19. Some of them share their feelings and suffering online via different online social media networks such as Twitter. Due to… read more here.
Keywords: network; social media; depression; hierarchical convolutional ... See more keywords
MSFCA-Net: A Multi-Scale Feature Convolutional Attention Network for Segmenting Crops and Weeds in the Field
Sign Up to like & getrecommendations! Published in 2023 at "Agriculture"
DOI: 10.3390/agriculture13061176
Abstract: Weed control has always been one of the most important issues in agriculture. The research based on deep learning methods for weed identification and segmentation in the field provides necessary conditions for intelligent point-to-point spraying… read more here.
Keywords: multi scale; attention network; segmentation; convolutional attention ... See more keywords