Ikuti
Bailey Kong
Bailey Kong
Ronin Institute
Email yang diverifikasi di ronininstitute.org - Beranda
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Dikutip oleh
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Conditional generative adversarial networks (cGANs) for near real-time precipitation estimation from multispectral GOES-16 satellite imageries—PERSIANN-cGAN
N Hayatbini, B Kong, K Hsu, P Nguyen, S Sorooshian, G Stephens, ...
Remote Sensing 11 (19), 2193, 2019
642019
Cross-domain image matching with deep feature maps
B Kong, J Supanc̆ic̆ III, D Ramanan, CC Fowlkes
International Journal of Computer Vision 127 (11), 1738-1750, 2019
572019
Fast convolutional sparse coding (FCSC)
B Kong, CC Fowlkes
Department of Computer Science, University of California, Irvine, Tech. Rep 3, 2014
452014
Cross-domain forensic shoeprint matching
B Kong, J Supanc̆ic̆, D Ramanan, CC Fowlkes
British Machine Vision Conference (BMVC), 2017
352017
Creating a Forensic Database of Shoeprints from Online Shoe-Tread Photos
S Shafique, B Kong, S Kong, C Fowlkes
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023
72023
A Deep Learning Framework for Precipitation Estimation from GOES-16 multispectral satellite imagery-Application of the conditional Generative Adversarial Networks (cGANs)
N Hayatbini, B Kong, KL Hsu, P Nguyen, S Sorooshian, GL Stephens
AGU Fall Meeting Abstracts 2019, H31P-1978, 2019
22019
Application of Generative Adversarial Networks (GANs) for Precipitation Forecasting
N Hayatbini, L Delle Monache, B Kong, F Cannon, W Chapman, ...
AGU Fall Meeting Abstracts 2020, A043-0008, 2020
12020
Energy-based spherical sparse coding
B Kong, CC Fowlkes
arXiv preprint arXiv:1710.01820, 2017
12017
ShoeRinsics: Shoeprint Prediction for Forensics with Intrinsic Decomposition.
S Shafique, B Kong, S Kong, CC Fowlkes
CoRR, 2022
2022
Learning Robust Features and Metrics for Image Classification and Matching
B Kong
University of California, Irvine, 2018
2018
Creating a Forensic Database of Shoeprints from Online Shoe Tread Photos (Supplementary Material)
S Shafique, B Kong, S Kong, C Fowlkes
Supplementary Material: Cross-Domain Forensic Shoeprint Matching
B Kong, D Ramanan, C Fowlkes
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