Results 281 to 290 of about 15,311,076 (365)

Temporal Ultrasound Image Enhancement for Kidney Diagnosis

, 2017
Pawan Shivan Othman
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Clathrin-MediatedEndocytosis for Enhanced ApoptosisInduction and Cellular Imaging in Triple-Negative Breast Cancer byCasein-Protected Blue-Emissive Carbon Dots

Bijaideep Dutta (17394968), Neena G. Shetake (17364598), Abhishek Sharma (144862), Kaustava Bhattacharyya (1774258), Badri N. Pandey (17364601), Puthusserickal A. Hassan (12118954), Kanhu C. Barick (6920282)   +6 more
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Underwater Image Enhancement Using a Diffusion Model with Adversarial Learning. [PDF]

J Imaging
Ding X, Chen X, Sui Y, Wang Y, Zhang J.
europepmc   +1 more source

D-PerceptCT: Deep Perceptual Enhancement for Low-Dose CT Images [PDF]

Nabila, Taifour Yousra, Beghdadi, Azeddine, Luong, Marie, Ming, Zuheng, Zaidi, Habib, Cheikh, Faouzi Alaya   +5 more
openalex  

Adaptive low-light image enhancement using Interval-Valued Intuitionistic Fuzzy Set optimized by Reptile Search Algorithm. [PDF]

Front Artif Intell
Yogambaram H, Sivabalakrishnan M, Balaji S.   +2 more
europepmc   +1 more source

Adversarial attacks dataset for low light image enhancement. [PDF]

Data Brief
Martinez A, Olague M, Olague G, Hernandez E, Lopez-Arredondo JC.   +4 more
europepmc   +1 more source

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Underwater Image Enhancement via Minimal Color Loss and Locally Adaptive Contrast Enhancement

IEEE Transactions on Image Processing, 2022
Underwater images typically suffer from color deviations and low visibility due to the wavelength-dependent light absorption and scattering. To deal with these degradation issues, we propose an efficient and robust underwater image enhancement method ...
Weishi Zhang, Peixian Zhuang, Hai-Han Sun   +2 more
exaly   +2 more sources

Underwater Image Enhancement With Reinforcement Learning

IEEE Journal of Oceanic Engineering
In this article, we develop an underwater image enhancement framework based on reinforcement learning. To do this, we model the underwater image enhancement as a Markov decision process (MDP), in which states are represented by image feature maps ...
Shixin Sun, Ming Xiang, Cai Luo
exaly   +2 more sources