1 citations · 1 across the 10 of their papers we have counts for
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Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model
Yu-Fan Lin, Bo-Cheng Qiu, Chia-Ming Lee +1
Accurate detection and segmentation of gastrointestinal bleeding are critical for diagnosing diseases such as peptic ulcers and colorectal cancer. This study proposes a two-stage f…
CSAKD: Knowledge Distillation with Cross Self-Attention for Hyperspectral and Multispectral Image Fusion
Chih-Chung Hsu, Chih-Chien Ni, Chia-Ming Lee +1
Hyperspectral imaging, capturing detailed spectral information for each pixel, is pivotal in diverse scientific and industrial applications. Yet, the acquisition of high-resolution…
Real-Time Compressed Sensing for Joint Hyperspectral Image Transmission and Restoration for CubeSat
Chih-Chung Hsu, Chih-Yu Jian, Eng-Shen Tu +2
This paper addresses the challenges associated with hyperspectral image (HSI) reconstruction from miniaturized satellites, which often suffer from stripe effects and are computatio…
Progressive Alignment with VLM-LLM Feature to Augment Defect Classification for the ASE Dataset
Chih-Chung Hsu, Chia-Ming Lee, Chun-Hung Sun +1
Traditional defect classification approaches are facing with two barriers. (1) Insufficient training data and unstable data quality. Collecting sufficient defective sample is expen…
MISS: Memory-efficient Instance Segmentation Framework By Visual Inductive Priors Flow Propagation
Chih-Chung Hsu, Chia-Ming Lee
Instance segmentation, a cornerstone task in computer vision, has wide-ranging applications in diverse industries. The advent of deep learning and artificial intelligence has under…
Augment Before Copy-Paste: Data and Memory Efficiency-Oriented Instance Segmentation Framework for Sport-scenes
Chih-Chung Hsu, Chia-Ming Lee, Ming-Shyen Wu
Instance segmentation is a fundamental task in computer vision with broad applications across various industries. In recent years, with the proliferation of deep learning and artif…