Cheng-Hao Tu

Computer Science · The Ohio State University

Mid career · publishing since 2005Rising activity

Domain Adaptation and Few-Shot Learning Advanced Image and Video Retrieval Techniques Multimodal Machine Learning Applications Video Surveillance and Tracking Methods Human Pose and Action Recognition

Publications

Citations

303

Est. group size

—

Recurring co-author estimate

Active years

Publishing since 2005

Research summary

AI-generated

This researcher works in computer science on machine learning topics such as hashing methods for fast image/data retrieval, continual (lifelong) learning where models learn new tasks without forgetting old ones, model compression for efficient deep learning, and facial/action recognition. Recent work also touches on information extraction from text, including a 2025 paper on entity relation extraction in ancient Chinese texts. The research combines practical efficiency concerns (compressing and pruning neural networks) with core learning problems (adapting to new data, hashing for search).

Deep learning to hash / image retrievalContinual and lifelong learningNeural network compression and pruningFacial action and pose recognitionText and information extraction

Publication output peaked in 2019 with a burst of activity, declined through 2020-2023 with some gaps, and shows a modest uptick in 2024 before slowing again in 2025.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence

Publications per year over the last 10 years — averaging 1.4/year recently

Recent publications

Multi-step Fusion of Relation Type Information and Multi-Task Decoding for Entity Relation Extraction in ancient Chinese
2025
Learning Binary Hash Codes Based on Adaptable Label Representations
IEEE Transactions on Neural Networks and Learning Systems · 2021
SemanticHash: Hash Coding Via Semantics-Guided Label Prototype Learning
IEEE Transactions on Artificial Intelligence · 2021
Defect Detection Using Deep Lifelong Learning
2021
Pruning Depthwise Separable Convolutions for MobileNet Compression
2020
Extending Conditional Convolution Structures For Enhancing Multitasking Continual Learning
Asia-Pacific Signal and Information Processing Association Annual Summit and Conference · 2020
Compacting, Picking and Growing for Unforgetting Continual Learning
arXiv (Cornell University) · 2019
Compacting, Picking and Growing for Unforgetting Continual Learning
arXiv (Cornell University) · 2019
IdenNet: Identity-Aware Facial Action Unit Detection
2019
Adaptive Labeling for Deep Learning to Hash
2019
Adaptive Labeling For Hash Code Learning Via Neural Networks
2019
Supervised Representation Hash Codes Learning
Communications in computer and information science · 2019
Pruning Depthwise Separable Convolutions for Extra Efficiency Gain of Lightweight Models
2019
Two-Stage Multi-Task Deep Convolutional Neural Networks for Robot Arm Grasping
2019
Equivalent Scanning Network of Unpadded CNNs
IEEE Signal Processing Letters · 2018

Publishes in

arXiv (Cornell University)×6
IEEE Transactions on Neural Networks and Learning Systems×1
IEEE Transactions on Artificial Intelligence×1
IEEE Signal Processing Letters×1
Asia-Pacific Signal and Information Processing Association Annual Summit and Conference×1

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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 19, 2026.

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