Zobrazeno 1 - 10
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pro vyhledávání: '"A. Tharun"'
The work introduces a bio-inspired leader-follower system based on an innovative mechanism proposed as software latching that aims to improve collaboration and coordination between a leader agent and the associated autonomous followers. The system ut
Externí odkaz:
http://arxiv.org/abs/2405.11659
Object tracking is a fundamental task in computer vision with broad practical applications across various domains, including traffic monitoring, robotics, and autonomous vehicle tracking. In this project, we aim to develop a sophisticated aerial vehi
Externí odkaz:
http://arxiv.org/abs/2405.11655
Preference-aligned robot navigation in human environments is typically achieved through learning-based approaches, utilizing user feedback or demonstrations for personalization. However, personal preferences are subject to change and might even be co
Externí odkaz:
http://arxiv.org/abs/2404.04857
Large language models (LLMs) have the remarkable ability to solve new tasks with just a few examples, but they need access to the right tools. Retrieval Augmented Generation (RAG) addresses this problem by retrieving a list of relevant tools for a gi
Externí odkaz:
http://arxiv.org/abs/2312.05708
Autor:
Singh, Vivek, Reddy, Tharun Kumar
Drowsiness state of a driver is a topic of extensive discussion due to its significant role in causing traffic accidents. This research presents a novel approach that combines Fuzzy Common Spatial Patterns (CSP) optimised Phase Cohesive Sequence (PCS
Externí odkaz:
http://arxiv.org/abs/2312.00479
Foresighted robot navigation in dynamic indoor environments with cost-efficient hardware necessitates the use of a lightweight yet dependable controller. So inferring the scene dynamics from sensor readings without explicit object tracking is a pivot
Externí odkaz:
http://arxiv.org/abs/2310.19670
Autor:
Geraedts, Scott, Brand, Erica, Dean, Thomas R., Eastham, Sebastian, Elkin, Carl, Engberg, Zebediah, Hager, Ulrike, Langmore, Ian, McCloskey, Kevin, Ng, Joe Yue-Hei, Platt, John C., Sankar, Tharun, Sarna, Aaron, Shapiro, Marc, Goyal, Nita
Persistent contrails make up a large fraction of aviation's contribution to global warming. We describe a scalable, automated detection and matching (ADM) system to determine from satellite data whether a flight has made a persistent contrail. The AD
Externí odkaz:
http://arxiv.org/abs/2308.02707
Autor:
Meisburger, Nicholas, Lakshman, Vihan, Geordie, Benito, Engels, Joshua, Ramos, David Torres, Pranav, Pratik, Coleman, Benjamin, Meisburger, Benjamin, Gupta, Shubh, Adunukota, Yashwanth, Medini, Tharun, Shrivastava, Anshumali
Efficient large-scale neural network training and inference on commodity CPU hardware is of immense practical significance in democratizing deep learning (DL) capabilities. Presently, the process of training massive models consisting of hundreds of m
Externí odkaz:
http://arxiv.org/abs/2303.17727
Autor:
Sharma, Shivam, Kulkarni, Atharva, Suresh, Tharun, Mathur, Himanshi, Nakov, Preslav, Akhtar, Md. Shad, Chakraborty, Tanmoy
Memes can sway people's opinions over social media as they combine visual and textual information in an easy-to-consume manner. Since memes instantly turn viral, it becomes crucial to infer their intent and potentially associated harmfulness to take
Externí odkaz:
http://arxiv.org/abs/2301.11219
Autor:
Sharma, Shivam, Agarwal, Siddhant, Suresh, Tharun, Nakov, Preslav, Akhtar, Md. Shad, Chakraborty, Tanmoy
Memes are powerful means for effective communication on social media. Their effortless amalgamation of viral visuals and compelling messages can have far-reaching implications with proper marketing. Previous research on memes has primarily focused on
Externí odkaz:
http://arxiv.org/abs/2212.00715