no code implementations • 1 Jun 2022 • Zahra Mirikharaji, Catarina Barata, Kumar Abhishek, Alceu Bissoto, 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).
no code implementations • 7 Apr 2022 • Kumar Abhishek, Colin J. Brown, Ghassan Hamarneh
Modern deep learning training procedures rely on model regularization techniques such as data augmentation methods, which generate training samples that increase the diversity of data and richness of label information.
no code implementations • 3 Jun 2021 • Kumar Abhishek, Ganesh Ghalme, Sujit Gujar, Yadati Narahari
An algorithm can select a subset of arms from the \emph{availability set} (sleeping bandits) and receive the corresponding reward along with semi-bandit feedback (combinatorial bandits).
1 code implementation • 2 May 2021 • Mengliu Zhao, Jeremy Kawahara, Kumar Abhishek, Sajjad Shamanian, Ghassan Hamarneh
Our lesion tracking algorithm achieves an average matching accuracy of 88% on a set of detected corresponding pairs of prominent lesions of subjects imaged in different poses, and an average longitudinal accuracy of 71% when encompassing additional errors due to lesion detection.
no code implementations • 9 Feb 2021 • Ayush Deva, Kumar Abhishek, Sujit Gujar
We show that after a certain number of rounds, $\tau$, \newalgo\ outputs a subset of agents that satisfy the average quality constraint with a high probability.
no code implementations • 14 Dec 2020 • Zahra Mirikharaji, Kumar Abhishek, Saeed Izadi, Ghassan Hamarneh
To this end, we propose an ensemble of Bayesian fully convolutional networks (FCNs) for the segmentation task by considering two major factors in the aggregation of multiple ground truth annotations: (1) handling contradictory annotations in the training data originating from inter-annotator disagreements and (2) improving confidence calibration through the fusion of base models' predictions.
1 code implementation • 26 Oct 2020 • Kumar Abhishek, Ghassan Hamarneh
The segmentation of skin lesions is a crucial task in clinical decision support systems for the computer aided diagnosis of skin lesions.
1 code implementation • 23 Mar 2020 • Kumar Abhishek, Ghassan Hamarneh, Mark S. Drew
The semantic segmentation of skin lesions is an important and common initial task in the computer aided diagnosis of dermoscopic images.
no code implementations • 26 Feb 2020 • Kumar Abhishek, Shweta Jain, Sujit Gujar
It is in the best interest of the center to select an ad that has a high expected value (i. e., probability of getting a click $\times$ value it derives from a click of the ad).
no code implementations • 28 Nov 2019 • Weina Jin, Mostafa Fatehi, Kumar Abhishek, Mayur Mallya, Brian Toyota, Ghassan Hamarneh
We believe that these technical approaches will facilitate the development of a fully-functional AI tool in the clinical care of patients with gliomas.
no code implementations • 16 Nov 2019 • Saeid Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh
To test the effectiveness of the proposed idea and compare it with other competing methods, we design several test scenarios, such as classification performance, uncertainty, out-of-distribution, and robustness analyses.
no code implementations • 16 Oct 2019 • Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen, Julien Cohen-Adad, Ghassan Hamarneh
The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class.
no code implementations • 4 Oct 2019 • Kumar Abhishek, Sneha Maheshwari, Sujit Gujar
In this report, we aim to exemplify concentration inequalities and provide easy to understand proofs for it.
no code implementations • 13 Jun 2019 • Kumar Abhishek, Ghassan Hamarneh
Skin lesion segmentation is a vital task in skin cancer diagnosis and further treatment.
no code implementations • 4 Apr 2019 • Saied Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh
Although numerous improvements have been made in the field of image segmentation using convolutional neural networks, the majority of these improvements rely on training with larger datasets, model architecture modifications, novel loss functions, and better optimizers.
1 code implementation • CVPR 2019 • Saeid Asgari Taghanaki, Kumar Abhishek, Shekoofeh Azizi, Ghassan Hamarneh
The linear and non-flexible nature of deep convolutional models makes them vulnerable to carefully crafted adversarial perturbations.
no code implementations • 12 Jan 2019 • Kumar Abhishek, Ashok Yogi
Format detection of news videos plays an important role in news video analysis.