Results 91 to 100 of about 18,768,334 (232)
Customized m-RCNN and hybrid deep classifier for liver cancer segmentation and classification
HeliyonDiagnosing liver disease presents a significant medical challenge in impoverished countries, with over 30 billion individuals succumbing to it each year.
Rashid Khan +5 more
doaj +1 more source
UDAPA: A Lightweight Adapter for Robust Underwater Image Enhancement via Input‐Side Alignment
IET Image Processing, Volume 20, Issue 1, January/December 2026.We propose UDAPA, a lightweight adapter framework for robust underwater image enhancement via input‐side alignment. Rather than modifying the pre‐trained backbone, UDAPA adapts degraded inputs toward a feature distribution that is more compatible with the frozen pre‐trained model.
Hui Zhang, Zhaolong Gao, Jinjiang Li
wiley +1 more source
A joint image dehazing and segmentation model
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2019 Objects and their feature identification in hazy or foggy weather conditions has been of interest in the last decades. Improving image visualization by removing weather influence factors for easy image postprocessing, such as object detection, has benefits for human assistance systems.
Haider Ali 0004 +3 more
openaire +1 more source
Image Dehazing Using a Convolutional Autoencoder Network with Integrated Convolutional Block Attention [PDF]
Journal of Artificial Intelligence and Data MiningOne of the challenges in digital image processing that we face today is the presence of haze in images. This challenge is particularly prominent in imaging areas with humid and rainy weather compared to other locations.
Homayoun Rastegar, Hassan Khotanlou
doaj +1 more source
IET Image Processing, Volume 20, Issue 1, January/December 2026.We propose a task‐driven adaptive image enhancement method and a feature enhancement strategy (DuoEnhance). This method performs dehazing through adaptive image enhancement and combines it with dilated‐aware weighted convolution to improve the model's perception of blurred edges and low‐contrast regions, enabling object detection on images captured by ...
Xuejuan Han +3 more
wiley +1 more source
UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning
, 2022 While the wisdom of training an image dehazing model on synthetic hazy data can alleviate the difficulty of collecting real-world hazy/clean image pairs, it brings the well-known domain shift problem.
Qin, Jing +6 more
core
Enhancing Surveillance Vision with Multi-Layer Deep Learning Representation
MathematicsThis paper aimed to develop a method for generating sand–dust removal and dehazed images utilizing CycleGAN, facilitating object identification on roads under adverse weather conditions such as heavy dust or haze, which severely impair visibility ...
Dong-Min Son, Sung-Hak Lee
doaj +1 more source
Fast No-reference Deep Image Dehazing
Machine Vision and ApplicationsAbstract This paper presents a deep learning method for image dehazing and clarification.The main advantages of the method are high computational speed and usingupaired image data for training. The method adapts the Zero-DCE approach for the image dehazing problem and uses high-order curves to adjust the dynamicrange of images and achieve ...
Hongyi Qin, Alexander G. Belyaev
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Dark Channel Prior Based Image Dehazing using Different Transmission Map Refinement Methods
International Journal of Innovative Technology and Exploring Engineering, 2019 Due to existence of haze, the image quality is degraded in the environment. Removal of haze is called dehazing. To dehaze an image Dark Channel Prior is recommended. Dark Channel Prior is an observation, that an image has few pixels whose intensity value
semanticscholar +1 more source
UNDERWATER IMAGE ENHANCEMENT THROUGH DEHAZING AND COLOR CORRECTION TECHNIQUES
, 2023 Underwater photography and videography suffer from significant challenges due to the inherent properties of water, such as light absorption, scattering, and color distortion.
K.Kumar swamy, A.Srirupa, Ch.Kavya , B.Sravya,Ch. Varshini
core +1 more source