A practical impossibility of prediction of signs of DCT coefficients is generally accepted. Therefore each coded sign of DCT coefficients occupies usually 1 bit of memory in compr...
Nikolay N. Ponomarenko, Andriy V. Bazhyna, Karen O...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
A new inter-processor communication architecture for chip multiprocessors is proposed which has a low area cost, flexible routing capability, and supports globally asynchronous loc...
Hashing, which tries to learn similarity-preserving binary codes for data representation, has been widely used for efficient nearest neighbor search in massive databases due to i...
Distributed PRocessing in Mobile Environments (DPRiME) is a framework for processing large data sets across an ad-hoc network. Developed to address the shortcomings of Google’s ...
Sean McRoskey, James Notwell, Nitesh V. Chawla, Ch...