Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
This paper presents a learning based method for automatic extraction of the major cortical sulci from MRI volumes or extracted surfaces. Instead of using a few pre-defined rules su...
Songfeng Zheng, Zhuowen Tu, Alan L. Yuille, Allan ...
Abstract—Hyperspectral unmixing aims at identifying the hidden spectral signatures (or endmembers) and their corresponding proportions (or abundances) from an observed hyperspect...
We present an algorithm for solving a general min-cut, twoway partitioning problem subject to timing constraints. The problem is formulated as a constrained programming problem an...
The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal differenc...
Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong ...