Abstract: Hyperspectral remote sensing images exhibit high dimensionality, a large volume of data, and significant redundant information. Before using deep learning methods for ground monitoring and ...
The numbers tell a striking story. Forty-three percent of companies now use AI for hiring—nearly double last year's 26%. Yet ...
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Issues are used to track todos, bugs, feature requests, and more.
The mathematical foundation of post-quantum cryptography primarily relies on complex mathematical problems, such as the shortest vector problem (SVP) and closest vector problem (CVP) within lattice ...
The development of new technologies in smart cities is often hailed as it becomes a necessity to solve many problems like energy consumption and transportation. Wireless networks are part of these ...
Treatment of acute stroke, before a distinction can be made between ischemic and hemorrhagic types, is challenging. Whether very early blood-pressure control in the ambulance improves outcomes among ...
Attribute reduction is a research hotspot in rough set theory. Traditional heuristic attribute reduction methods add the most important attribute to the decision attribute set each time, resulting in ...
The Data Reduction for Science program seeks applications to explore potentially high-impact approaches in the development and use of data reduction techniques and algorithms to facilitate more ...
Abstract: The current attribute reduction algorithms for information systems are difficult to handle imbalanced data with default values. Therefore, to address the shortcomings of traditional ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback