Zobrazeno 1 - 10
of 416 962
pro vyhledávání: '"Reddy BE"'
Autor:
Böhlen, Marc, Sughiarta, Gede, Kurnianingsih, Atiek, Gopaladinne, Srikar Reddy, Shrivastava, Sujay, Gorla, Hemanth Kumar Reddy
This paper describes spatially aware Artificial Intelligence, GeoAI, tailored for small organizations such as NGOs in resource constrained contexts where access to large datasets, expensive compute infrastructure and AI expertise may be restricted. W
Externí odkaz:
http://arxiv.org/abs/2408.17361
Autor:
Gudepu, Venkateswarlu, Chirumamilla, Bhargav, Chintapalli, Venkatarami Reddy, Castoldi, Piero, Valcarenghi, Luca, Tamma, Bheemarjuna Reddy, Kondepu, Koteswararao
Beyond fifth-generation (B5G) networks aim to support high data rates, low-latency applications, and massive machine communications. Artificial Intelligence/Machine Learning (AI/ML) can help to improve B5G network performance and efficiency. However,
Externí odkaz:
http://arxiv.org/abs/2408.14827
Autor:
Zhou, Guanglei, Korrapati, Bhargav, Reddy, Gaurav Rajavendra, Hu, Jiang, Chen, Yiran, Thakurta, Dipto G.
Generation of VLSI layout patterns is essential for a wide range of Design For Manufacturability (DFM) studies. In this study, we investigate the potential of generative machine learning models for creating design rule legal metal layout patterns. Ou
Externí odkaz:
http://arxiv.org/abs/2409.01348
Autor:
Prasad, K. Durga, Kumar, Chandan, Mishra, Sanjeev K., Reddy, P. Kalyana S., Kumar, Janmejay, Ladiya, Tinkal, Patel, Arpit, Bhardwaj, Anil
Publikováno v:
Journal of Spacecraft Technology, 34(2), July-Dec. 2023, Publisher: U.R.Rao.Satellite Centre, ISRO, Bangalore, ISSN: 0971-1600
Chandra Surface Thermophysical Experiment (ChaSTE) is one of the payloads flown onboard the Chandrayaan-3 lander. The objective of the experiment is in-situ investigation of thermal behaviour of outermost 100 mm layer of the lunar surface by deployin
Externí odkaz:
http://arxiv.org/abs/2409.00150
Publikováno v:
Asif Ali et. al. EPL 147 46002 (2024)
Electron correlation and long-range magnetic ordering have a significant impact on the electronic structure and physical properties of solids. Here, we investigate the electronic structure of ilmenite MnTiO$_{3}$ using room temperature photoemission
Externí odkaz:
http://arxiv.org/abs/2408.16301
Autor:
Bhogale, Kaushal Santosh, Mehendale, Deovrat, Parasa, Niharika, G, Sathish Kumar Reddy, Javed, Tahir, Kumar, Pratyush, Khapra, Mitesh M.
In this study, we tackle the challenge of limited labeled data for low-resource languages in ASR, focusing on Hindi. Specifically, we explore pseudo-labeling, by proposing a generic framework combining multiple ideas from existing works. Our framewor
Externí odkaz:
http://arxiv.org/abs/2408.14026
Accurate classification of celestial objects is essential for advancing our understanding of the universe. MargNet is a recently developed deep learning-based classifier applied to SDSS DR16 dataset to segregate stars, quasars, and compact galaxies u
Externí odkaz:
http://arxiv.org/abs/2408.13634
Autor:
Pepi, Chrysanthos, Godala, Bhargav Reddy, Tibrewala, Krishnam, Chacon, Gino, Gratz, Paul V., Jiménez, Daniel A., Pokam, Gilles A., August, David I.
Modern processors implement a decoupled front-end in the form of Fetch Directed Instruction Prefetching (FDIP) to avoid front-end stalls. FDIP is driven by the Branch Prediction Unit (BPU), relying on the BPU's accuracy and branch target tracking str
Externí odkaz:
http://arxiv.org/abs/2408.12592
Deep convolutional neural networks (CNNs) have achieved impressive performance in many computer vision tasks. However, their large model sizes require heavy computational resources, making pruning redundant filters from existing pre-trained CNNs an e
Externí odkaz:
http://arxiv.org/abs/2409.03777
Autor:
Berge, Siri Hegna, de Winter, Joost, Dodou, Dimitra, Afghari, Amir Pooyan, Papadimitriou, Eleonora, Reddy, Nagarjun, Dong, Yongqi, Raju, Narayana, Farah, Haneen
As automated vehicles (AVs) become increasingly popular, the question arises as to how cyclists will interact with such vehicles. This study investigated (1) whether cyclists spontaneously notice if a vehicle is driverless, (2) how well they perform
Externí odkaz:
http://arxiv.org/abs/2408.10064