TNNLS
Computer Vision & Pattern Recognition Artificial Intelligence
IEEE Transactions on Neural Networks and Learning Systems Call for Papers
Special Issue on
Effective Feature Fusion in Deep Neural Networks
https://cis.ieee.org/images/files/Documents/call-for-papers/tnnls/SI_EFDNN_TNNLS_CFP.pdf
Submission deadline: Nov. 30, 2020. First notification: Feb. 1, 2021
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Due to the powerful ability of learning hierarchical features, Deep Neural Networks (DNNs) have achieved great success in many intelligent perception systems with image data and/or point cloud data and have been widely used in developing robust automotive driving, visual surveillance, and human-machine interaction. For example, state-of-the-art performances in image classification, object detection, semantic segmentation, and cross-modal perception are obtained by different kinds of DNNs. To a great degree, the success of DNNs stems from properly fusing the hierarchical features which are diverse in semantic-levels, resolutions/scales, roles, sensitivity, and so on. Representative fusion schemes include dense connection, residual learning, skip connection, top-down feature pyramid, and attention-based feature weighting. However, there is a large room for developing more effective feature fusion to improve the performance of DNNs so that machine perception can approach or exceed human perception.
This special issue focuses on investigating problems and phenomena of existing feature fusion schemes, tackling the challenges of semantic gap and perception of hard objects and scenarios, and providing new ideas, theories, solutions, and insights for effective feature fusion in DNNs for image and/or point cloud data. The topics of interest include, but are not limited to:
IMPORTANT DATES
GUEST EDITORS
Yanwei Pang, Tianjin University, China, pyw@tju.edu.cn
Fahad Shahbaz Khan, Inception Institute of Artificial Intelligence, UAE, fahad.khan@liu.se
Xin Lu, Adobe Inc., USA, xinl@adobe.com
Fabio Cuzzolin, Oxford Brookes University, UK, fabio.cuzzolin@brookes.ac.uk
SUBMISSION INSTRUCTIONS