Search Results for author: Kumar Abhishek

Found 17 papers, 4 papers with code

A Survey on Deep Learning for Skin Lesion Segmentation

no code implementations1 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).

Lesion Segmentation Skin Lesion Segmentation +1

Multi-Sample $ζ$-mixup: Richer, More Realistic Synthetic Samples from a $p$-Series Interpolant

no code implementations7 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.

Data Augmentation Image Classification +1

Sleeping Combinatorial Bandits

no code implementations3 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).

Skin3D: Detection and Longitudinal Tracking of Pigmented Skin Lesions in 3D Total-Body Textured Meshes

1 code implementation2 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.

Lesion Detection

A Multi-Arm Bandit Approach To Subset Selection Under Constraints

no code implementations9 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.

D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application to Skin Lesion Segmentation

no code implementations14 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.

Lesion Segmentation Semantic Segmentation +1

Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation

1 code implementation26 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.

Lesion Segmentation Skin Lesion Segmentation

Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images

1 code implementation23 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.

Lesion Segmentation Semantic Segmentation +1

Designing Truthful Contextual Multi-Armed Bandits based Sponsored Search Auctions

no code implementations26 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).

Multi-Armed Bandits

Artificial Intelligence in Glioma Imaging: Challenges and Advances

no code implementations28 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.

Computed Tomography (CT) Image Imputation +1

Signed Input Regularization

no code implementations16 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.

Data Augmentation

Deep Semantic Segmentation of Natural and Medical Images: A Review

no code implementations16 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.

Medical Image Segmentation Scene Understanding +1

Introduction to Concentration Inequalities

no code implementations4 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.

Improved Inference via Deep Input Transfer

no code implementations4 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.

Lesion Segmentation Semantic Segmentation +1

Summarization and Visualization of Large Volumes of Broadcast Video Data

no code implementations12 Jan 2019 Kumar Abhishek, Ashok Yogi

Format detection of news videos plays an important role in news video analysis.

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