Xiao Hu

Orcid: 0000-0003-1128-4099

Affiliations:
  • Purdue University, West Lafayette, IN, USA


According to our database1, Xiao Hu authored at least 13 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
Evolution of Winning Solutions in the 2021 Low-Power Computer Vision Challenge.
Computer, August, 2023

2022
Why Accuracy is Not Enough: The Need for Consistency in Object Detection.
IEEE Multim., 2022

Directed Acyclic Graph-based Neural Networks for Tunable Low-Power Computer Vision.
Proceedings of the ISLPED '22: ACM/IEEE International Symposium on Low Power Electronics and Design, Boston, MA, USA, August 1, 2022

Efficient Computer Vision on Edge Devices with Pipeline-Parallel Hierarchical Neural Networks.
Proceedings of the 27th Asia and South Pacific Design Automation Conference, 2022

Irrelevant Pixels are Everywhere: Find and Exclude Them for More Efficient Computer Vision.
Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2021
Low-Power Multi-Camera Object Re-Identification using Hierarchical Neural Networks.
Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2021


2020
Observing Responses to the COVID-19 Pandemic using Worldwide Network Cameras.
CoRR, 2020

Crowdsourcing Detection of Sampling Biases in Image Datasets.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

A Large-Scale Annotated Mechanical Components Benchmark for Classification and Retrieval Tasks with Deep Neural Networks.
Proceedings of the Computer Vision - ECCV 2020, 2020

First-Person View Hand Segmentation of Multi-Modal Hand Activity Video Dataset.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019
Low-Power Computer Vision: Status, Challenges, and Opportunities.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2019

Low-Power Computer Vision: Status, Challenges, Opportunities.
CoRR, 2019


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