Author of the publication

Analysis of Gabor-Based Texture Features for the Identification of Breast Tumor Regions in Mammograms.

, , , , , and . CCIA, volume 269 of Frontiers in Artificial Intelligence and Applications, page 149-158. IOS Press, (2014)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

No persons found for author name Melendez, Jaime
add a person with the name Melendez, Jaime
 

Other publications of authors with the same name

Supervised texture segmentation through a multi-level pixel-based classifier based on specifically designed filters., , and . ICIP, page 2869-2872. IEEE, (2011)Automated localization of breast cancer in DCE-MRI., , , , , , and . Medical Image Analysis, 20 (1): 265-274 (2015)Localized Energy-Based Normalization of Medical Images: Application to Chest Radiography., , , , , and . IEEE Trans. Med. Imaging, 34 (9): 1965-1975 (2015)A Novel Multiple-Instance Learning-Based Approach to Computer-Aided Detection of Tuberculosis on Chest X-Rays., , , , , , , , , and . IEEE Trans. Med. Imaging, 34 (1): 179-192 (2015)Multi-level pixel-based texture classification through efficient prototype selection via normalized cut., , and . Pattern Recognition, 43 (12): 4113-4123 (2010)Application-independent feature selection for texture classification., , and . Pattern Recognition, 43 (10): 3282-3297 (2010)Computer-aided diagnosis of breast cancer via Gabor wavelet bank and binary-class SVM in mammographic images., , , and . J. Exp. Theor. Artif. Intell., 28 (1-2): 295-311 (2016)Gabor-based texture classification through efficient prototype selection via normalized cut., , and . ICIP, page 1385-1388. IEEE, (2009)On Adapting Pixel-based Classification to Unsupervised Texture Segmentation., , and . ICPR, page 854-857. IEEE Computer Society, (2010)Screening for Diabetic Retinopathy through Retinal Colour Fundus Images using Convolutional Neural Networks., , , , and . CCIA, volume 277 of Frontiers in Artificial Intelligence and Applications, page 259-262. IOS Press, (2015)