4 citations · 10 across the 6 of their papers we have counts for
10 papers
Vulnerability Due to Training Order in Split Learning
Harshit Madaan, Manish Gawali, Viraj Kulkarni +1
Split learning (SL) is a privacy-preserving distributed deep learning method used to train a collaborative model without the need for sharing of patient's raw data between clients.…
Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentations
Jitesh Seth, Rohit Lokwani, Viraj Kulkarni +2
Deep learning semantic segmentation algorithms can localise abnormalities or opacities from chest radiographs. However, the task of collecting and annotating training data is expen…
Comparative Evaluation of 3D and 2D Deep Learning Techniques for Semantic Segmentation in CT Scans
Abhishek Shivdeo, Rohit Lokwani, Viraj Kulkarni +2
Image segmentation plays a pivotal role in several medical-imaging applications by assisting the segmentation of the regions of interest. Deep learning-based approaches have been w…
Deep Learning Models for Calculation of Cardiothoracic Ratio from Chest Radiographs for Assisted Diagnosis of Cardiomegaly
Tanveer Gupte, Mrunmai Niljikar, Manish Gawali +3
We propose an automated method based on deep learning to compute the cardiothoracic ratio and detect the presence of cardiomegaly from chest radiographs. We develop two separate mo…
Comparison of Privacy-Preserving Distributed Deep Learning Methods in Healthcare
Manish Gawali, Arvind C S, Shriya Suryavanshi +5
In this paper, we compare three privacy-preserving distributed learning techniques: federated learning, split learning, and SplitFed. We use these techniques to develop binary clas…
Automated Detection of COVID-19 from CT Scans Using Convolutional Neural Networks
Rohit Lokwani, Ashrika Gaikwad, Viraj Kulkarni +2
COVID-19 is an infectious disease that causes respiratory problems similar to those caused by SARS-CoV (2003). Currently, swab samples are being used for its diagnosis. The most co…
Quantum Computing Methods for Supervised Learning
Viraj Kulkarni, Milind Kulkarni, Aniruddha Pant
The last two decades have seen an explosive growth in the theory and practice of both quantum computing and machine learning. Modern machine learning systems process huge volumes o…
Role of Edge Device and Cloud Machine Learning in Point-of-Care Solutions Using Imaging Diagnostics for Population Screening
Amit Kharat, Vinay Duddalwar, Krishna Saoji +8
Edge devices are revolutionizing diagnostics. Edge devices can reside within or adjacent to imaging tools such as digital Xray, CT, MRI, or ultrasound equipment. These devices are…
Automatic Grading of Knee Osteoarthritis on the Kellgren-Lawrence Scale from Radiographs Using Convolutional Neural Networks
Sudeep Kondal, Viraj Kulkarni, Ashrika Gaikwad +2
The severity of knee osteoarthritis is graded using the 5-point Kellgren-Lawrence (KL) scale where healthy knees are assigned grade 0, and the subsequent grades 1-4 represent incre…
Survey of Personalization Techniques for Federated Learning
Viraj Kulkarni, Milind Kulkarni, Aniruddha Pant
Federated learning enables machine learning models to learn from private decentralized data without compromising privacy. The standard formulation of federated learning produces on…