1 code implementation • 1 Jun 2022 • Zahra Mirikharaji, Kumar Abhishek, Alceu Bissoto, Catarina Barata, Sandra Avila, Eduardo Valle, M. Emre Celebi, Ghassan Hamarneh
We analyze these works along several dimensions, including input data (datasets, preprocessing, and synthetic data generation), model design (architecture, modules, and losses), and evaluation aspects (data annotation requirements and segmentation performance).
1 code implementation • 26 Dec 2020 • Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger, Huiyu Zhou, Ruili Wang, M. Emre Celebi, Jie Yang
However, there is a lack of comprehensive review in this field, especially lack of a collection of GANs loss-variant, evaluation metrics, remedies for diverse image generation, and stable training.
no code implementations • 27 Mar 2019 • Ziping Jiang, Paul L. Chazot, M. Emre Celebi, Danny Crookes, Richard Jiang
Behavioural phenotyping of Drosophila is an important means in biological and medical research to identify genetic, pathologic or psychologic impact on animal behaviour.
17 code implementations • 9 Feb 2019 • Noel Codella, Veronica Rotemberg, Philipp Tschandl, M. Emre Celebi, Stephen Dusza, David Gutman, Brian Helba, Aadi Kalloo, Konstantinos Liopyris, Michael Marchetti, Harald Kittler, Allan Halpern
This work summarizes the results of the largest skin image analysis challenge in the world, hosted by the International Skin Imaging Collaboration (ISIC), a global partnership that has organized the world's largest public repository of dermoscopic images of skin.
12 code implementations • 13 Oct 2017 • Noel C. F. Codella, David Gutman, M. Emre Celebi, Brian Helba, Michael A. Marchetti, Stephen W. Dusza, Aadi Kalloo, Konstantinos Liopyris, Nabin Mishra, Harald Kittler, Allan Halpern
This article describes the design, implementation, and results of the latest installment of the dermoscopic image analysis benchmark challenge.
no code implementations • 28 Jan 2016 • Nabin K. Mishra, M. Emre Celebi
The development of advanced technologies in the areas of image processing and machine learning have given us the ability to allow distinction of malignant melanoma from the many benign mimics that require no biopsy.
no code implementations • 12 Sep 2014 • M. Emre Celebi, Hassan A. Kingravi
Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results.
no code implementations • 26 Dec 2013 • M. Emre Celebi, Quan Wen, Sae Hwang, Hitoshi Iyatomi, Gerald Schaefer
Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions.
no code implementations • 28 Apr 2013 • M. Emre Celebi, Hassan A. Kingravi
Experiments on a large and diverse collection of data sets from the UCI Machine Learning Repository demonstrate that Var-Part and PCA-Part are highly competitive with one of the best random initialization methods to date, i. e., k-means++, and that the proposed approach significantly improves the performance of both hierarchical methods.
1 code implementation • 10 Sep 2012 • M. Emre Celebi, Hassan A. Kingravi, Patricio A. Vela
K-means is undoubtedly the most widely used partitional clustering algorithm.