Zobrazeno 1 - 10
of 134 866
pro vyhledávání: '"P, Reddy"'
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
The detection of bias in natural language processing (NLP) is a critical challenge, particularly with the increasing use of large language models (LLMs) in various domains. This paper introduces GUS-Net, an innovative approach to bias detection that
Externí odkaz:
http://arxiv.org/abs/2410.08388
Autor:
Vanteddu, Punith Reddy, Nava, Gabriele, Bergonti, Fabio, L'Erario, Giuseppe, Paolino, Antonello, Pucci, Daniele
Co-design optimization strategies usually rely on simplified robot models extracted from CAD. While these models are useful for optimizing geometrical and inertial parameters for robot control, they might overlook important details essential for prot
Externí odkaz:
http://arxiv.org/abs/2410.07963
Autor:
PN, Aravinda Reddy, Ramachandra, Raghavendra, Venkatesh, Sushma, Rao, Krothapalli Sreenivasa, Mitra, Pabitra, Krishna, Rakesh
Face recognition systems (FRS) can be compromised by face morphing attacks, which blend textural and geometric information from multiple facial images. The rapid evolution of generative AI, especially Generative Adversarial Networks (GAN) or Diffusio
Externí odkaz:
http://arxiv.org/abs/2410.07625
Gumbel Rao Monte Carlo based Bi-Modal Neural Architecture Search for Audio-Visual Deepfake Detection
Autor:
PN, Aravinda Reddy, Ramachandra, Raghavendra, Rao, Krothapalli Sreenivasa, Rathod, Pabitra Mitra Vinod
Deepfakes pose a critical threat to biometric authentication systems by generating highly realistic synthetic media. Existing multimodal deepfake detectors often struggle to adapt to diverse data and rely on simple fusion methods. To address these ch
Externí odkaz:
http://arxiv.org/abs/2410.06543
Reasoning about spatial relationships between objects is essential for many real-world robotic tasks, such as fetch-and-delivery, object rearrangement, and object search. The ability to detect and disambiguate different objects and identify their loc
Externí odkaz:
http://arxiv.org/abs/2410.07394
Autor:
Sanjaripour, Sogol, Hemmati, Shoubaneh, Mobasher, Bahram, Canalizo, Gabriela, Barish, Barry, Shivaei, Irene, Coil, Alison L., Chartab, Nima, Jafariyazani, Marziye, Reddy, Naveen A., Azadi, Mojegan
The growing volume of data produced by large astronomical surveys necessitates the development of efficient analysis techniques capable of effectively managing high-dimensional datasets. This study addresses this need by demonstrating some applicatio
Externí odkaz:
http://arxiv.org/abs/2410.07354
Autor:
Tan, Jinzhe, Westermann, Hannes, Pottanigari, Nikhil Reddy, Šavelka, Jaromír, Meeùs, Sébastien, Godet, Mia, Benyekhlef, Karim
Mediation is a dispute resolution method featuring a neutral third-party (mediator) who intervenes to help the individuals resolve their dispute. In this paper, we investigate to which extent large language models (LLMs) are able to act as mediators.
Externí odkaz:
http://arxiv.org/abs/2410.07053
Autor:
Reddy, Kovvuri Sai Gopal, Saran, Bodduluri, Adityaja, A. Mudit, Shigwan, Saurabh J., Kumar, Nitin, Mukherjee, Snehasis
The data-hungry approach of supervised classification drives the interest of the researchers toward unsupervised approaches, especially for problems such as medical image segmentation, where labeled data are difficult to get. Motivated by the recent
Externí odkaz:
http://arxiv.org/abs/2410.06114