scispace - formally typeset
Search or ask a question
Institution

Vaughn College of Aeronautics and Technology

EducationNew York, New York, United States
About: Vaughn College of Aeronautics and Technology is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Gravitational microlensing & Planetary system. The organization has 727 authors who have published 708 publications receiving 14082 citations. The organization is also known as: College of Aeronautics.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, the Lawrence Livermore DYNA3D code has been improved to accurately model hypervelocity impact, and the SESAME Equation of State has been implemented to improve the material modelling.

9 citations

Journal ArticleDOI
TL;DR: In this article, a new method of speed control for sewing machines used in the shoe industry was studied in a series of experiments and the skill requirements of the task were examined and the new control was tested both in the laboratory and in the factory.
Abstract: A new method of speed control for sewing machines used in the shoe industry was studied in a series of experiments. The skill requirements of the task were examined and the new control was tested both in the laboratory and in the factory. The justification for this kind of investigation is discussed.

9 citations

Journal ArticleDOI
09 Aug 2018-Sensors
TL;DR: To solve the problems of color distortion and structure blurring in images acquired by sensors during bad weather, an image dehazing algorithm based on feature learning is put forward to improve the quality of sensor images.
Abstract: To solve the problems of color distortion and structure blurring in images acquired by sensors during bad weather, an image dehazing algorithm based on feature learning is put forward to improve the quality of sensor images. First, we extracted the multiscale structure features of the haze images by sparse coding and the various haze-related color features simultaneously. Then, the generative adversarial network (GAN) was used for sample training to explore the mapping relationship between different features and the scene transmission. Finally, the final haze-free image was obtained according to the degradation model. Experimental results show that the method has obvious advantages in its detail recovery and color retention. In addition, it effectively improves the quality of sensor images.

9 citations


Authors

Showing all 732 results

NameH-indexPapersCitations
Xiang Zhang1541733117576
Denis J. Sullivan6133214092
To. Saito511839392
Arthur H. Lefebvre411234896
Michele Meo402235557
Robin S. Langley402635601
Ning Qin372835011
Holger Babinsky332424068
B. S. Gaudi31642560
Philip J. Longhurst29802578
Michael Gaster27663998
Don Harris261292537
To. Saito25562362
John F. O'Connell22891763
Rade Vignjevic21841563
Network Information
Related Institutions (5)
Langley Research Center
37.6K papers, 821.6K citations

76% related

Technion – Israel Institute of Technology
79.3K papers, 2.6M citations

76% related

Northwestern Polytechnical University
56K papers, 657K citations

76% related

Beihang University
73.5K papers, 975.6K citations

75% related

Harbin Institute of Technology
109.2K papers, 1.6M citations

74% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20236
20223
202145
202033
201934
201841