Te Hu

Orcid: 0000-0002-8975-0363

According to our database1, Te Hu authored at least 14 papers between 2014 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Robust and Stealthy Traffic Sign Adversarial Attacks via Diffusion-Augmented I-FGSM.
IEEE Access, 2026

2025
The Outline of Deception: Physical Adversarial Attacks on Traffic Signs Using Edge Patches.
CoRR, December, 2025

Privacy Protection of Automotive Location Data Based on Format-Preserving Encryption of Geographical Coordinates.
CoRR, October, 2025

Exploration of project-based learning model for digital image processing education based on design, implementation, and evaluation.
Educ. Inf. Technol., September, 2025

A 28-nm 28.8-TOPS/W Attention-Based NN Processor With Correlative CIM Ring Architecture and Dataflow-Reshaped Digital-Assisted CIM Array.
IEEE J. Solid State Circuits, January, 2025

2024
Familiar Feelings: Emotion Look Development on Pixar's Inside Out 2.
Proceedings of the ACM SIGGRAPH 2024 Talks, 2024

2023
TT@CIM: A Tensor-Train In-Memory-Computing Processor Using Bit-Level-Sparsity Optimization and Variable Precision Quantization.
IEEE J. Solid State Circuits, March, 2023

Creating Elemental Characters: From Sparks to Fire.
Proceedings of the ACM SIGGRAPH 2023 Talks, 2023

2021
TIMAQ: A Time-Domain Computing-in-Memory-Based Processor Using Predictable Decomposed Convolution for Arbitrary Quantized DNNs.
IEEE J. Solid State Circuits, 2021

15.4 A 5.99-to-691.1TOPS/W Tensor-Train In-Memory-Computing Processor Using Bit-Level-Sparsity-Based Optimization and Variable-Precision Quantization.
Proceedings of the IEEE International Solid-State Circuits Conference, 2021

2020
A Time-Domain Computing-in-Memory based Processor using Predictable Decomposed Convolution for Arbitrary Quantized DNNs.
Proceedings of the IEEE Asian Solid-State Circuits Conference, 2020

2019
Identify of Spatial Similarity of Electroencephalography (EEG) during Working-Memory Maintenance.
Proceedings of the 27th European Signal Processing Conference, 2019

2018
Exploring the Neural Pattern in EEG Records of Material-specific Memory Maintenance by Deep Learning.
Proceedings of the 14th International Conference on Natural Computation, 2018

2014
Influential Factors of Spatial Distribution of Wheat Yield in China During 1978-2007: A Spatial Econometric Analysis.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014


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