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HyperEAST: An Enhanced Attention-Based Spectral-Spatial Transformer with Self-Supervised Pretraining for Hyperspectral Image Classification

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2025

We propose HyperEAST, an enhanced attention-based spectral-spatial transformer with self-supervised pretraining for hyperspectral image classification.

Recommended citation: Tang, Jialin; Ma, Nan; Jia, Chen; Tian, Rui; Guo, Yanhui. (2025). "HyperEAST: An Enhanced Attention-Based Spectral-Spatial Transformer with Self-Supervised Pretraining for Hyperspectral Image Classification." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 22241-22255.
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MAS-LLaVA: Motion-Aware Adaptive Sampling for Training-Free Video Large Language Models

Presented at IEEE International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), 2026

MAS-LLaVA introduces motion-aware adaptive sampling for training-free video large language models.

Recommended citation: Tang, Jialin; Bai, Yu. (2026). "MAS-LLaVA: Motion-Aware Adaptive Sampling for Training-Free Video Large Language Models." IEEE International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA).
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Optimizing Energy Management Strategy for EV Wireless Charging Efficiency Using Proximal Policy Optimization

Presented at IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC), 2026

This work applies proximal policy optimization to energy management for EV wireless charging efficiency.

Recommended citation: George, Ava; Tang, Jialin. (2026). "Optimizing Energy Management Strategy for EV Wireless Charging Efficiency Using Proximal Policy Optimization." IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC).
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Regression-Based Modeling of Antisense Oligonucleotide Efficacy Using Sequence, Structural, and Off-Target Features

Presented at IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC), 2026

This work models ASO efficacy using sequence, structural, and off-target features.

Recommended citation: George, Ava; Bai, Yu; Tang, Jialin. (2026). "Regression-Based Modeling of Antisense Oligonucleotide Efficacy Using Sequence, Structural, and Off-Target Features." IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC).
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HyperMODE: A Continuous-Depth Spectral-Spatial Modeling Framework with Mamba and Neural Ordinary Differential Equations for Hyperspectral Image Classification

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2026

HyperMODE is a continuous-depth spectral-spatial modeling framework for hyperspectral image classification.

Recommended citation: Tang, Jialin; Lou, Yunduan; Guo, Yanhui; Bai, Yu. (2026). "HyperMODE: A Continuous-Depth Spectral-Spatial Modeling Framework with Mamba and Neural Ordinary Differential Equations for Hyperspectral Image Classification." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 19. doi: 10.1109/JSTARS.2026.3705708.
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Jialin (Jaylen) Tang