Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
To realize context aware applications for smart home environments, it is necessary to recognize function or usage of objects as well as categories of them. On conventional researc...
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
This paper presents a multimodal learning system that can ground spoken names of objects in their physical referents and learn to recognize those objects simultaneously from natur...
Identifying or matching the surface color of a moving object in surveillance video is critical for achieving reliable object-tracking and searching. Traditional color models provi...
Gang Wu, Amir Rahimi, Edward Y. Chang, Kingshy Goh...