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data-driven

Coarse-to-Fine CNN for Image Super-Resolution

By: 
Chunwei Tian, Yong Xu, Wangmeng Zuo, Bob Zhang, Lunke Fei, Chia-Wen Lin

A coarse-to-fine SR CNN (CFSRCNN) consisting of a stack of feature extraction blocks (FEBs), an enhancement block (EB), a construction block (CB) and, a feature refinement block (FRB) is proposed to learn a robust SR model.

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Collaborative Cloud and Edge Mobile Computing in C-RAN Systems

By: 
Seok-Hwan Park, Seongah Jeong, Jinyeop Na, Osvaldo Simeone, Shlomo Shamai

To handle the various types of tasks in the upcoming cellular services, we can design the system with both cloud and edge computing capabilities, where the computational tasks can be partially offloaded to the ENs and the CP.

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Revitalizing Underwater Image Enhancement in the Deep Learning Era

By: 
Dr. Chongyi Li

Underwater image enhancement has drawn considerable attention in both image processing and underwater vision. Due to the complicated underwater environment and lighting conditions, enhancing underwater image is a challenging problem. 

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