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DLL-GAN: Degradation-level-based learnable adversarial loss for image enhancement.

, , , и . Expert Syst. Appl., 237 (Part C): 121666 (марта 2024)

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Kajo Niggestich

Kajo Schommer

Kajohn Boonrod

Kajo Neukirchen

Kajo Schausten

 

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SVD-Based Tensor-Completion Technique for Background Initialization., , , и . IEEE Trans. Image Process., 27 (6): 3114-3126 (2018)MFGAN: towards a generic multi-kernel filter based adversarial generator for image restoration., , , и . Int. J. Mach. Learn. Cybern., 15 (3): 1113-1136 (марта 2024)An adaptive block-based matching algorithm for crowd motion sequences., , и . Multimedia Tools Appl., 77 (2): 1783-1809 (2018)Incremental Tensor-Based Completion Method for Detection of Stationary Foreground Objects., , и . IEEE Trans. Circuits Syst. Video Techn., 29 (5): 1325-1338 (2019)Self-Motion-Assisted Tensor Completion Method for Background Initialization in Complex Video Sequences., , и . IEEE Trans. Image Process., (2020)Frequency-Aware SVD Decomposition and its Application to Color Magnification and Motion Denoising., , , и . IEEE Access, (2021)Spatiotemporal CNN with Pyramid Bottleneck Blocks: Application to eye blinking detection., , , и . Neural Networks, (2022)History Based Incremental Singular Value Decomposition for Background Initialization and Foreground Segmentation., , и . CIARP, том 14469 из Lecture Notes in Computer Science, стр. 63-75. Springer, (2023)Tensor-Based Approach for Background-Foreground Separation in Maritime Sequences., , и . IEEE Trans. Intell. Transp. Syst., 22 (11): 7115-7128 (2021)Tensor based completion meets adversarial learning: A win-win solution for change detection on unseen videos., , , и . Comput. Vis. Image Underst., (2023)