activity
20212024
most citedFoodWise: Food Waste Reduction and Behavior Change on Campus with Data Visualization and Gamification

19 citations · 41 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

Non-parametric regularization for class imbalance federated medical image classification

Jeffry Wicaksana, Zengqiang Yan, Kwang-Ting Cheng

Limited training data and severe class imbalance pose significant challenges to developing clinically robust deep learning models. Federated learning (FL) addresses the former by e…

cs.HC2023★ 19 cited

FoodWise: Food Waste Reduction and Behavior Change on Campus with Data Visualization and Gamification

Yue Yu, Sophia Yi, Xi Nan +6

Food waste presents a substantial challenge with significant environmental and economic ramifications, and its severity on campus environments is of particular concern. In response…

cs.CV2023★ 2 cited

FCA: Taming Long-tailed Federated Medical Image Classification by Classifier Anchoring

Jeffry Wicaksana, Zengqiang Yan, Kwang-Ting Cheng

Limited training data and severe class imbalance impose significant challenges to developing clinically robust deep learning models. Federated learning (FL) addresses the former by…

cs.LG2022★ 8 cited

SDQ: Stochastic Differentiable Quantization with Mixed Precision

Xijie Huang, Zhiqiang Shen, Shichao Li +5

In order to deploy deep models in a computationally efficient manner, model quantization approaches have been frequently used. In addition, as new hardware that supports mixed bitw…

cs.CV2022★ 10 cited

FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation

Jeffry Wicaksana, Zengqiang Yan, Dong Zhang +4

The purpose of federated learning is to enable multiple clients to jointly train a machine learning model without sharing data. However, the existing methods for training an image…

cs.MM2021★ 2 cited

Automated Vision-Based Wellness Analysis for Elderly Care Centers

Xijie Huang, Jeffry Wicaksana, Shichao Li +1

The growth in the aging population requires caregivers to improve both efficiency and quality of healthcare. In this study, we develop an automatic, vision-based system for monitor…