Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Tamboli, Dipesh"'
Sepsis, a life-threatening condition triggered by the body's exaggerated response to infection, demands urgent intervention to prevent severe complications. Existing machine learning methods for managing sepsis struggle in offline scenarios, exhibiti
Externí odkaz:
http://arxiv.org/abs/2403.07309
This paper presents the Ensemble Nucleotide Byte-level Encoder-Decoder (ENBED) foundation model, analyzing DNA sequences at byte-level precision with an encoder-decoder Transformer architecture. ENBED uses a sub-quadratic implementation of attention
Externí odkaz:
http://arxiv.org/abs/2311.02333
Autor:
Pal, Debabrata, More, Deeptej, Bhargav, Sai, Tamboli, Dipesh, Aggarwal, Vaneet, Banerjee, Biplab
Publikováno v:
ICCV 2023
Few-shot learning has made impressive strides in addressing the crucial challenges of recognizing unknown samples from novel classes in target query sets and managing visual shifts between domains. However, existing techniques fall short when it come
Externí odkaz:
http://arxiv.org/abs/2309.12814
Multi-task Imitation Learning (MIL) aims to train a policy capable of performing a distribution of tasks based on multi-task expert demonstrations, which is essential for general-purpose robots. Existing MIL algorithms suffer from low data efficiency
Externí odkaz:
http://arxiv.org/abs/2305.12633
We tackle the problem of image inpainting in the remote sensing domain. Remote sensing images possess high resolution and geographical variations, that render the conventional inpainting methods less effective. This further entails the requirement of
Externí odkaz:
http://arxiv.org/abs/2202.05988
Autor:
Tamboli, Dipesh
This document summarizes different visual explanations methods such as CAM, Grad-CAM, Localization using Multiple Instance Learning - Saliency-based methods, Saliency-driven Class-Impressions, Muting pixels in input image - Adversarial methods and Ac
Externí odkaz:
http://arxiv.org/abs/2106.08366
In this paper, we propose a data-free method of extracting Impressions of each class from the classifier's memory. The Deep Learning regime empowers classifiers to extract distinct patterns (or features) of a given class from training data, which is
Externí odkaz:
http://arxiv.org/abs/2007.15861
Autor:
Vishal, Mukesh Kumar, Tamboli, Dipesh, Patil, Abhijeet, Saluja, Rohit, Banerjee, Biplab, Sethi, Amit, Raju, Dhandapani, Kumar, Sudhir, Sahoo, R N, Chinnusamy, Viswanathan, Adinarayana, J
Development of either drought-resistant or drought-tolerant varieties in rice (Oryza sativa L.), especially for high yield in the context of climate change, is a crucial task across the world. The need for high yielding rice varieties is a prime conc
Externí odkaz:
http://arxiv.org/abs/2004.02498
Publikováno v:
J. Phys. D: Appl. Phys. 53 49LT01 (2020)
Metasurfaces is an emerging field that enables the manipulation of light by an ultra-thin structure composed of sub-wavelength antennae and fulfills an important requirement for miniaturized optical elements. Finding a new design for a metasurface or
Externí odkaz:
http://arxiv.org/abs/2003.12402
Breast cancer has the highest mortality among cancers in women. Computer-aided pathology to analyze microscopic histopathology images for diagnosis with an increasing number of breast cancer patients can bring the cost and delays of diagnosis down. D
Externí odkaz:
http://arxiv.org/abs/2003.00823