Sherwood and Zeger proposed a source-channel coding system where the source code is an embedded bitstream and the channel code is a product code such that each row code is a conca...
In this paper we evaluate the effectiveness of two likelihood normalization techniques, the Background Model Set (BMS) and the Universal Background Model (UBM), for improving perf...
Large margin classifiers have demonstrated their advantages in many visual learning tasks, and have attracted much attention in vision and image processing communities. In this pa...
We combine multiple description (MD) quantization, entropy coding, and data partitioning to improve the error resiliency of images over varying packet loss channels. Our proposed ...
We propose XSEED, a synopsis of path queries for cardinality estimation that is accurate, robust, efficient, and adaptive to memory budgets. XSEED starts from a very small kernel,...