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Pi-Cheng Hsiu

Researcher at Center for Information Technology

Publications -  95
Citations -  1428

Pi-Cheng Hsiu is an academic researcher from Center for Information Technology. The author has contributed to research in topics: Mobile device & Energy consumption. The author has an hindex of 18, co-authored 91 publications receiving 1171 citations. Previous affiliations of Pi-Cheng Hsiu include National Taiwan University & Academia Sinica.

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Proceedings ArticleDOI

SSR-NET: A compact soft stagewise regression network for age estimation

TL;DR: A novel CNN model called Soft Stagewise Regression Network (SSR-Net) for age estimation from a single image with a compact model size is presented and its performance approaches those of the state-of-the-art methods whose model sizes are often more than 1500× larger.
Proceedings ArticleDOI

Age-based PCM wear leveling with nearly zero search cost

TL;DR: An efficient wear-leveling design that is compatible with existing virtual memory management is presented and two implementations, namely, bucket-based and array-based wear leveling, with nearly zero search cost are proposed to tradeoff time and space complexity.
Journal ArticleDOI

Distributed Throughput Optimization for ZigBee Cluster-Tree Networks

TL;DR: This paper presents an adoptive-parent-based framework for a ZigBee cluster-tree network to increase bandwidth utilization without generating any extra message exchange, and develops a distributed algorithm that is fully compatible with the ZigBee standard.
Journal ArticleDOI

A Mobility-Aware Node Deployment and Tree Construction Framework for ZigBee Wireless Networks

TL;DR: The results show that the approach can construct ZigBee tree topologies with a high data delivery ratio and low routing overhead, and the effectiveness of network topologies constructed under the framework is demonstrated through comprehensive ns-2 simulations based on two real-world scenarios.
Journal ArticleDOI

Dynamic Backlight Scaling Optimization: A Cloud-Based Energy-Saving Service for Mobile Streaming Applications

TL;DR: This paper model the problem as a dynamic backlight scaling optimization problem, proposes algorithms to solve the fundamental problem and proves the optimality in terms of energy savings, and presents a cloud-based energy-saving service.