Zobrazeno 1 - 10
of 22 662
pro vyhledávání: '"Gani A."'
Autor:
Gani A. Jaelani
Publikováno v:
Wacana: Journal of the Humanities of Indonesia, Vol 25, Iss 1, Pp 65-85 (2024)
Since their arrival in the seventeenth century, through the nature of their calling – from the examination of the sick and efforts to acquire knowledge of local medicines – European physicians in the Netherlands East Indies inevitably encountered
Externí odkaz:
https://doaj.org/article/3a30e767c92e4a378f722a6981bb6664
Autor:
Newlin, Nancy R., Schilling, Kurt, Koudoro, Serge, Chandio, Bramsh Qamar, Kanakaraj, Praitayini, Moyer, Daniel, Kelly, Claire E., Genc, Sila, Chen, Jian, Yang, Joseph Yuan-Mou, Wu, Ye, He, Yifei, Zhang, Jiawei, Zeng, Qingrun, Zhang, Fan, Adluru, Nagesh, Nath, Vishwesh, Pathak, Sudhir, Schneider, Walter, Gade, Anurag, Rathi, Yogesh, Hendriks, Tom, Vilanova, Anna, Chamberland, Maxime, Pieciak, Tomasz, Ciupek, Dominika, Vega, Antonio Tristán, Aja-Fernández, Santiago, Malawski, Maciej, Ouedraogo, Gani, Machnio, Julia, Ewert, Christian, Thompson, Paul M., Jahanshad, Neda, Garyfallidis, Eleftherios, Landman, Bennett A.
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2024)
White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (DW-MRI) to qualitatively identify changes in white matter microstructu
Externí odkaz:
http://arxiv.org/abs/2411.09618
Autor:
Munasinghe, Shehan, Gani, Hanan, Zhu, Wenqi, Cao, Jiale, Xing, Eric, Khan, Fahad Shahbaz, Khan, Salman
Fine-grained alignment between videos and text is challenging due to complex spatial and temporal dynamics in videos. Existing video-based Large Multimodal Models (LMMs) handle basic conversations but struggle with precise pixel-level grounding in vi
Externí odkaz:
http://arxiv.org/abs/2411.04923
Publikováno v:
Russian Journal of Agricultural and Socio-Economic Sciences, Vol 112, Iss 4, Pp 160-166 (2021)
Drift gill net is a rectangular net. Knowledge of the measure of gear selectivity is very important for fisheries management and ecology. Common water fishing activities in South Kalimantan are generally carried out in rivers, swamps, lakes or reserv
Externí odkaz:
https://doaj.org/article/b51cbd4eed9e4ba7a34231f09e2859a3
The Greenland Ice Sheet (GrIS) has emerged as a significant contributor to global sea level rise, primarily due to increased meltwater runoff. Supraglacial lakes, which form on the ice sheet surface during the summer months, can impact ice sheet dyna
Externí odkaz:
http://arxiv.org/abs/2410.05638
Autor:
Nawaz, Umair, Awais, Muhammad, Gani, Hanan, Naseer, Muzammal, Khan, Fahad, Khan, Salman, Anwer, Rao Muhammad
Capitalizing on vast amount of image-text data, large-scale vision-language pre-training has demonstrated remarkable zero-shot capabilities and has been utilized in several applications. However, models trained on general everyday web-crawled data of
Externí odkaz:
http://arxiv.org/abs/2410.01407
Autor:
Haghighi, Yasaman, Demonsant, Celine, Chalimourdas, Panagiotis, Naeini, Maryam Tavasoli, Munoz, Jhon Kevin, Bacca, Bladimir, Suter, Silvan, Gani, Matthieu, Alahi, Alexandre
In this paper, we introduce HEADS-UP, the first egocentric dataset collected from head-mounted cameras, designed specifically for trajectory prediction in blind assistance systems. With the growing population of blind and visually impaired individual
Externí odkaz:
http://arxiv.org/abs/2409.20324
The conventional modus operandi for adapting pre-trained vision-language models (VLMs) during test-time involves tuning learnable prompts, ie, test-time prompt tuning. This paper introduces Test-Time Low-rank adaptation (TTL) as an alternative to pro
Externí odkaz:
http://arxiv.org/abs/2407.15913
The recent developments in Large Multi-modal Video Models (Video-LMMs) have significantly enhanced our ability to interpret and analyze video data. Despite their impressive capabilities, current Video-LMMs have not been evaluated for anomaly detectio
Externí odkaz:
http://arxiv.org/abs/2406.10326
Autor:
Ali, Sahara, Hasan, Uzma, Li, Xingyan, Faruque, Omar, Sampath, Akila, Huang, Yiyi, Gani, Md Osman, Wang, Jianwu
This survey paper covers the breadth and depth of time-series and spatiotemporal causality methods, and their applications in Earth Science. More specifically, the paper presents an overview of causal discovery and causal inference, explains the unde
Externí odkaz:
http://arxiv.org/abs/2404.05746