Zobrazeno 1 - 10
of 8 305
pro vyhledávání: '"Awasthi, P."'
Autor:
Pham, Trong Thang, Nguyen, Tien-Phat, Ikebe, Yuki, Awasthi, Akash, Deng, Zhigang, Wu, Carol C., Nguyen, Hien, Le, Ngan
Medical eye-tracking data is an important information source for understanding how radiologists visually interpret medical images. This information not only improves the accuracy of deep learning models for X-ray analysis but also their interpretabil
Externí odkaz:
http://arxiv.org/abs/2411.05780
Autor:
Awasthi, Pravesh Chndra, More, Jai, Pradhan, Akhila Kumar, Rao, Kumar, Sahu, Purushottam, Sankar, S. Uma
The occurrence of neutrino oscillations demands the existence of flavour violation in charged lepton sector. The relation between the branching ratios of different charged lepton flavour violating (CLFV) decay modes depends on the details of the neut
Externí odkaz:
http://arxiv.org/abs/2410.10490
The present study investigates the behaviour of the far-field sound radiated by low Mach number tip clearance flow induced by placing a stationary cambered airfoil adjacent to a stationary wall. The tip clearance heights ranged from 14% to 30% of the
Externí odkaz:
http://arxiv.org/abs/2410.01310
This work is a benchmark study for quantum-classical computing method with a real-world optimization problem from industry. The problem involves scheduling and balancing jobs on different machines, with a non-linear objective function. We first prese
Externí odkaz:
http://arxiv.org/abs/2408.01641
Predicting human gaze behavior within computer vision is integral for developing interactive systems that can anticipate user attention, address fundamental questions in cognitive science, and hold implications for fields like human-computer interact
Externí odkaz:
http://arxiv.org/abs/2407.00129
Human-AI collaboration to identify and correct perceptual errors in chest radiographs has not been previously explored. This study aimed to develop a collaborative AI system, CoRaX, which integrates eye gaze data and radiology reports to enhance diag
Externí odkaz:
http://arxiv.org/abs/2406.19686
A core component present in many successful neural network architectures, is an MLP block of two fully connected layers with a non-linear activation in between. An intriguing phenomenon observed empirically, including in transformer architectures, is
Externí odkaz:
http://arxiv.org/abs/2406.17989
Medical image segmentation is a critical task in healthcare applications, and U-Nets have demonstrated promising results. This work delves into the understudied aspect of receptive field (RF) size and its impact on the U-Net and Attention U-Net archi
Externí odkaz:
http://arxiv.org/abs/2406.16701
Autor:
Kazemi, Mehran, Dikkala, Nishanth, Anand, Ankit, Devic, Petar, Dasgupta, Ishita, Liu, Fangyu, Fatemi, Bahare, Awasthi, Pranjal, Guo, Dee, Gollapudi, Sreenivas, Qureshi, Ahmed
With the continuous advancement of large language models (LLMs), it is essential to create new benchmarks to effectively evaluate their expanding capabilities and identify areas for improvement. This work focuses on multi-image reasoning, an emerging
Externí odkaz:
http://arxiv.org/abs/2406.09175
Autor:
Bohnet, Bernd, Swersky, Kevin, Liu, Rosanne, Awasthi, Pranjal, Nova, Azade, Snaider, Javier, Sedghi, Hanie, Parisi, Aaron T, Collins, Michael, Lazaridou, Angeliki, Firat, Orhan, Fiedel, Noah
We explore the use of long-context capabilities in large language models to create synthetic reading comprehension data from entire books. Previous efforts to construct such datasets relied on crowd-sourcing, but the emergence of transformers with a
Externí odkaz:
http://arxiv.org/abs/2406.00179