Zobrazeno 1 - 10
of 1 655
pro vyhledávání: '"Thapaliya A"'
Publikováno v:
Ekológia (Bratislava), Vol 43, Iss 1, Pp 112-119 (2024)
Wildlife crime has emerged as one of the most crucial threats to biodiversity conservation and is particularly severe in south and southeast Asia. Addressing the ever-increasing challenges of wildlife crime in Nepal requires strategies informed by ri
Externí odkaz:
https://doaj.org/article/3d0a6bf750764f16bba37579dd8e7619
Autor:
Thapaliya, Bishal, Nguyen, Anh, Lu, Yao, Xie, Tian, Grudetskyi, Igor, Lin, Fudong, Valkanas, Antonios, Liu, Jingyu, Chakraborty, Deepayan, Fehri, Bilel
Classifying nodes in a graph is a common problem. The ideal classifier must adapt to any imbalances in the class distribution. It must also use information in the clustering structure of real-world graphs. Existing Graph Neural Networks (GNNs) have n
Externí odkaz:
http://arxiv.org/abs/2410.11765
Vision-Language Models (VLMs) have shown impressive performance in vision tasks, but adapting them to new domains often requires expensive fine-tuning. Prompt tuning techniques, including textual, visual, and multimodal prompting, offer efficient alt
Externí odkaz:
http://arxiv.org/abs/2410.05239
Modern day studies show a high degree of correlation between high yielding crop varieties and plants with upright leaf angles. It is observed that plants with upright leaf angles intercept more light than those without upright leaf angles, leading to
Externí odkaz:
http://arxiv.org/abs/2408.00749
Autor:
Thapaliya, Bishal, Miller, Robyn, Chen, Jiayu, Wang, Yu-Ping, Akbas, Esra, Sapkota, Ram, Ray, Bhaskar, Suresh, Pranav, Ghimire, Santosh, Calhoun, Vince, Liu, Jingyu
Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technique pivotal for understanding human neural mechanisms of intricate cognitive processes. Most rs-fMRI studies compute a single static functional connectivity matrix a
Externí odkaz:
http://arxiv.org/abs/2405.15805
Autor:
Ohib, Riyasat, Thapaliya, Bishal, Dziugaite, Gintare Karolina, Liu, Jingyu, Calhoun, Vince, Plis, Sergey
In this work, we propose Salient Sparse Federated Learning (SSFL), a streamlined approach for sparse federated learning with efficient communication. SSFL identifies a sparse subnetwork prior to training, leveraging parameter saliency scores computed
Externí odkaz:
http://arxiv.org/abs/2405.09037
Foundation Vision-Language Models (VLMs) trained using large-scale open-domain images and text pairs have recently been adapted to develop Vision-Language Segmentation Models (VLSMs) that allow providing text prompts during inference to guide image s
Externí odkaz:
http://arxiv.org/abs/2405.06196
Autor:
Thapaliya, Bishal, Akbas, Esra, Chen, Jiayu, Sapkota, Raam, Ray, Bhaskar, Suresh, Pranav, Calhoun, Vince, Liu, Jingyu
Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured without relying
Externí odkaz:
http://arxiv.org/abs/2311.03520
Autor:
Adhikari, Rabin, Dhakal, Manish, Thapaliya, Safal, Poudel, Kanchan, Bhandari, Prasiddha, Khanal, Bishesh
Accurate segmentation is essential for echocardiography-based assessment of cardiovascular diseases (CVDs). However, the variability among sonographers and the inherent challenges of ultrasound images hinder precise segmentation. By leveraging the jo
Externí odkaz:
http://arxiv.org/abs/2309.12829
Autor:
Poudel, Kanchan, Dhakal, Manish, Bhandari, Prasiddha, Adhikari, Rabin, Thapaliya, Safal, Khanal, Bishesh
Medical image segmentation allows quantifying target structure size and shape, aiding in disease diagnosis, prognosis, surgery planning, and comprehension.Building upon recent advancements in foundation Vision-Language Models (VLMs) from natural imag
Externí odkaz:
http://arxiv.org/abs/2308.07706