3 citations · 3 across the 3 of their papers we have counts for
5 papers
Learning to Compensate: A Deep Neural Network Framework for 5G Power Amplifier Compensation
Po-Yu Chen, Hao Chen, Yi-Min Tsai +6
Owing to the complicated characteristics of 5G communication system, designing RF components through mathematical modeling becomes a challenging obstacle. Moreover, such mathematic…
Network Space Search for Pareto-Efficient Spaces
Min-Fong Hong, Hao-Yun Chen, Min-Hung Chen +5
Network spaces have been known as a critical factor in both handcrafted network designs or defining search spaces for Neural Architecture Search (NAS). However, an effective space…
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency
Cheng-Ming Chiang, Yu Tseng, Yu-Syuan Xu +13
Recently, image enhancement and restoration have become important applications on mobile devices, such as super-resolution and image deblurring. However, most state-of-the-art netw…
Unified Dynamic Convolutional Network for Super-Resolution with Variational Degradations
Yu-Syuan Xu, Shou-Yao Roy Tseng, Yu Tseng +2
Deep Convolutional Neural Networks (CNNs) have achieved remarkable results on Single Image Super-Resolution (SISR). Despite considering only a single degradation, recent studies al…
Architecture-aware Network Pruning for Vision Quality Applications
Wei-Ting Wang, Han-Lin Li, Wei-Shiang Lin +2
Convolutional neural network (CNN) delivers impressive achievements in computer vision and machine learning field. However, CNN incurs high computational complexity, especially for…