no code implementations • 18 Jan 2024 • Vandan Gorade, Sparsh Mittal, Debesh Jha, Rekha Singhal, Ulas Bagci
This paper presents a novel approach that synergies spatial and spectral representations to enhance domain-generalized medical image segmentation.
no code implementations • IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023 • Onkar Susladkar, Gayatri Deshmukh, Dhruv Makwana, Sparsh Mittal, R Sai Chandra Teja, Rekha Singhal
We introduce a novel network, GAFNet (Global Attention Fourier Net), which learns through large-scale pre-training over three image-text datasets (COCO, SBU, and CC-3M), for achieving high performance on downstream vision and language tasks.
1 code implementation • 26 Oct 2022 • Onkar Susladkar, Dhruv Makwana, Gayatri Deshmukh, Sparsh Mittal, Sai Chandra Teja R, Rekha Singhal
Further, we use a novel multi-headed decoder that generates a high-pass filtered image and a segmentation map, in addition to a text-free image.
no code implementations • 27 Oct 2021 • Varad Pimpalkhute, Amey Pandit, Mayank Mishra, Rekha Singhal
Meta Learning has been in focus in recent years due to the meta-learner model's ability to adapt well and generalize to new tasks, thus, reducing both the time and data requirements for learning.
no code implementations • 31 May 2019 • Rekha Singhal, Gautam Shroff, Mukund Kumar, Sharod Roy, Sanket Kadarkar, Rupinder virk, Siddharth Verma, Vartika Tiwari
In this paper, we present iPrescribe, a scalable low-latency architecture for recommending 'next-best-offers' in an online setting.
no code implementations • 24 May 2019 • Rekha Singhal, Nathan Zhang, Luigi Nardi, Muhammad Shahbaz, Kunle Olukotun
Modern real-time business analytic consist of heterogeneous workloads (e. g, database queries, graph processing, and machine learning).