All Outputs (3)

Manifold Regularized Experimental Design for Active Learning (2016)
Journal Article
Zhang, L., Shum, H. P., & Shao, L. (2017). Manifold Regularized Experimental Design for Active Learning. IEEE Transactions on Image Processing, 26(2), 969-981. https://doi.org/10.1109/tip.2016.2635440

Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many p... Read More about Manifold Regularized Experimental Design for Active Learning.

Validation of an ergonomic assessment method using Kinect data in real workplace conditions (2016)
Journal Article
Plantard, P., Shum, H. P., Le Pierres, A.-S., & Multon, F. (2017). Validation of an ergonomic assessment method using Kinect data in real workplace conditions. Applied Ergonomics: Human Factors in Technology and Society, 65, 562-569. https://doi.org/10.1016/j.apergo.2016.10.015

Evaluating potential musculoskeletal disorders risks in real workstations is challenging as the environment is cluttered, which makes it difficult to accurately assess workers' postures. Being marker-free and calibration-free, Microsoft Kinect is a p... Read More about Validation of an ergonomic assessment method using Kinect data in real workplace conditions.

Discriminative Semantic Subspace Analysis for Relevance Feedback (2016)
Journal Article
Zhang, L., Shum, H., & Shao, L. (2016). Discriminative Semantic Subspace Analysis for Relevance Feedback. IEEE Transactions on Image Processing, 25(3), 1275-1287. https://doi.org/10.1109/tip.2016.2516947

Content-based image retrieval (CBIR) has attracted much attention during the past decades for its potential practical applications to image database management. A variety of relevance feedback (RF) schemes have been designed to bridge the gap between... Read More about Discriminative Semantic Subspace Analysis for Relevance Feedback.