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Resultats globals: 5 registres trobats en 0.03 segons.
Articles, 3 registres trobats
Documents de recerca, 2 registres trobats
Articles 3 registres trobats  
1.
15 p, 901.4 KB An efficient hybrid approach for medical images enhancement / Saroj, Sushil Kumar (Madan Mohan Malaviya University of Technology) ; Kumar, Rakesh (Madan Mohan Malaviya University of Technology) ; Singh, Nagendra Pratap (National Institute of Technology)
Medical images have various critical usages in the field of medical science and healthcare engineering. These images contain information about many severe diseases. Health professionals identify various diseases by observing the medical images. [...]
2022 - 10.5565/rev/elcvia.1574
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 21 Núm. 2 (2022) , p. 62-76 (Regular Issue)  
Registre complet - Creative Commons
2.
19 p, 1.3 MB Retinal Blood Vessels Segmentation using Fréchet PDF and MSMO Method / Kumar Saroj, Sushil (MMMUT gorakhpur) ; Kumar, Rakesh (Madan Mohan Malaviya University of Technology (Ïndia)) ; Singh, Nagendra Pratap (NIT, Hamirpur)
Blood vessels of retina contain information about many severe diseases like glaucoma, hypertension, obesity, diabetes etc. Health professionals use this information to detect and diagnose these diseases. [...]
2022 - 10.5565/rev/elcvia.1453
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 21 Núm. 1 (2022) , p. 28-46 (Regular Issue)  
Registre complet - Creative Commons
3.
15 p, 1.2 MB Identification of Suitable Contrast Enhancement Technique for Improving the Quality of Astrocytoma Histopathological Images / Dzulkifli, Fahmi Akmal (University Malaysia Perlis. School of Mechatronic Engineering)
Contrast enhancement plays an important part in image processing. In histology, the application of a contrast enhancement technique is necessary since it can help pathologists in diagnosing the sample slides by increasing the visibility of the morphological and features of cells in an image. [...]
2021 - 10.5565/rev/elcvia.1256
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 84-98 (Regular Issue)  
Registre complet - Creative Commons

Documents de recerca 2 registres trobats  
1.
11 p, 13.5 MB Nilut : conditional neural implicit 3d lookup tables for image enhancement / Conde, Marcos V. (University of Wurzburg. Computer Vision Lab) ; Vázquez i Corral, Javier (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació) ; Brown, Michael S. (York University) ; Timofte, Radu (University of Wurzburg. Computer Vision Lab)
3D lookup tables (3D LUTs) are a key component for image enhancement. Modern image signal processors (ISPs) have dedicated support for these as part of the camera rendering pipeline. Cameras typically provide multiple options for picture styles, where each style is usually obtained by applying a unique handcrafted 3D LUT. [...]
2024 - 10.48550/arXiv.2306.11920  
Registre complet - Creative Commons
2.
25.3 MB Document Image Enhancement and Recognition in Low Resource Scenarios : Application to Ciphers and Handwritten Text / Souibgui, Mohamed Ali ; Fornes Bisquerra, Alicia, dir. ; Yousri, Kassentini, dir. ; Lladós, Josep, dir.
En aquesta tesi proposem diferents contribucions per tal de millorar i reconèixer imatges de documents manuscrits històrics, especialment aquells amb escriptures rares, com els documents xifrats. A la primera part es presenten alguns models efectius d'extrem a extrem per millorar imatges de documents utilitzant models d'aprenentatge profund. [...]
En esta tesis proponemos diferentes contribuciones con el objetivo de mejorar y reconocer imágenes de documentos manuscritos históricos, especialmente aquellos con escrituras raras, como los documentos cifrados. [...]
In this thesis, we propose different contributions with the goal of enhancing and recognizing historical handwritten document images, especially the ones with rare scripts, such as cipher documents. In the first part, some effective end-to-end models for Document Image Enhancement (DIE) using deep learning models were presented. [...]
2022  
Registre complet - Creative Commons

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