Zobrazeno 1 - 10
of 1 044
pro vyhledávání: '"Vatsa, P."'
Autor:
Sultania, Dewang, Lu, Zhaoyu, Naik, Twisha, Dernoncourt, Franck, Yoon, David Seunghyun, Sharma, Sanat, Bui, Trung, Gupta, Ashok, Vatsa, Tushar, Suresha, Suhas, Verma, Ishita, Belavadi, Vibha, Chen, Cheng, Friedrich, Michael
Domain specific question answering is an evolving field that requires specialized solutions to address unique challenges. In this paper, we show that a hybrid approach combining a fine-tuned dense retriever with keyword based sparse search methods si
Externí odkaz:
http://arxiv.org/abs/2412.03736
Autor:
Shah, Shivalee, Vatsa, Mayank
This paper introduces a novel quantum diffusion model designed for Noisy Intermediate-Scale Quantum (NISQ) devices. Unlike previous methods, this model efficiently processes higher-dimensional images with complex pixel structures, even on qubit-limit
Externí odkaz:
http://arxiv.org/abs/2411.15973
Access to expert coaching is essential for developing technique in sports, yet economic barriers often place it out of reach for many enthusiasts. To bridge this gap, we introduce Poze, an innovative video processing framework that provides feedback
Externí odkaz:
http://arxiv.org/abs/2411.05734
The advent of edge computing is set to revolutionize cloud computing in various sectors, including Agriculture, Health, and more. AWS Greengrass Core Device plays a pivotal role in this transformative process by bridging connections between IoT devic
Externí odkaz:
http://arxiv.org/abs/2411.08914
Background: Full-field, quantitative visualization techniques, such as digital image correlation (DIC), have unlocked vast opportunities for experimental mechanics. However, DIC has traditionally been a surface measurement technique, and has not been
Externí odkaz:
http://arxiv.org/abs/2410.17493
Deep learning models, such as those used for face recognition and attribute prediction, are susceptible to manipulations like adversarial noise and unintentional noise, including Gaussian and impulse noise. This paper introduces CIAI, a Class-Indepen
Externí odkaz:
http://arxiv.org/abs/2409.19619
The dynamic collapse of pores under shock loading is thought to be directly related to hot spot generation and material failure, which is critical to the performance of porous energetic and structural materials. However, the shock compression respons
Externí odkaz:
http://arxiv.org/abs/2408.16931
Traditional deep learning models rely on methods such as softmax cross-entropy and ArcFace loss for tasks like classification and face recognition. These methods mainly explore angular features in a hyperspherical space, often resulting in entangled
Externí odkaz:
http://arxiv.org/abs/2408.02494
This research investigates biases in text-to-image (TTI) models for the Indic languages widely spoken across India. It evaluates and compares the generative performance and cultural relevance of leading TTI models in these languages against their per
Externí odkaz:
http://arxiv.org/abs/2408.00283
This research addresses the challenges of diagnosing chest X-rays (CXRs) at low resolutions, a common limitation in resource-constrained healthcare settings. High-resolution CXR imaging is crucial for identifying small but critical anomalies, such as
Externí odkaz:
http://arxiv.org/abs/2405.13370