1 citations · 1 across the 6 of their papers we have counts for
6 papers
EMBRACE: A Multi-task Framework for Comprehensive Quality Assessment in Cleavage-stage Embryo
Anwar Hussain Sofi, Jung-Hua Wang, Ming-Jer Chen +4
Cleavage-stage embryo assessment in in vitro fertilization requires the integrated interpretation of cytoplasmic fragmentation, developmental stage, and blastomere symmetry. Howeve…
RL-Ballast: Ship Ballast Water Path Planning and Clog Prediction via Reinforcement Learning
Ming-Kuan Lin, Yi-Chung Lai, Ming-Hsin Chiang +2
Under the Shipping 4.0 paradigm, autonomous and reduced-crew vessels require intelligent internal systems to maintain operational safety and structural stability. Ballast-water con…
BioVid: Autoregressive Video Generation with Biological Behavior Semantic Comprehension
Tsung-Wei Pan, Jung-Hua Wang
Video generation for biological behavior requires more than visually plausible motion: the duration of an action is itself a semantic property. Existing models usually rely on fixe…
Beyond Data Scarcity Optimizing R3GAN for Medical Image Generation from Small Datasets
Tsung-Wei Pan, Chang-Hong Wu, Jung-Hua Wang +3
Medical image datasets frequently exhibit significant class imbalance, a challenge that is further amplified by the inherently limited sample sizes that characterize clinical imagi…
AttnRegDeepLab: A Two-Stage Decoupled Framework for Interpretable Embryo Fragmentation Grading
Ming-Jhe Lee, Chang-Hong Wu, Jung-Hua Wang +3
Assessing embryo fragmentation is crucial for predicting IVF success, yet manual grading is prone to subjectivity, and existing AI models struggle with clinical interpretability an…
Federal Learning Framework for Quality Evaluation of Blastomere Cleavage
Jung-Hua Wang, Huai-Wen Chang, Rong-Yu Wu +3
This study addresses the issue of leveraging federated learning to improve data privacy and performance in IVF embryo selection. The EM (Expectation-Maximization) algorithm is inco…