Zobrazeno 1 - 10
of 210
pro vyhledávání: '"Gupta, Ananya"'
Publikováno v:
Clinical Nutrition Open Science, Vol 58, Iss , Pp 104-120 (2024)
Summary: Changes in taste have been perceived as a common side effect of different cancers and may lead to malnutrition. Hence, the importance of understanding cancer patients' sensory taste perceptions and its impact on nutritional status, quality o
Externí odkaz:
https://doaj.org/article/f5322e206c7545898505b6d90b357b0c
Deep Ensemble Convolutional Neural Networks has become a methodology of choice for analyzing medical images with a diagnostic performance comparable to a physician, including the diagnosis of Diabetic Retinopathy. However, commonly used techniques ar
Externí odkaz:
http://arxiv.org/abs/2211.03148
Autor:
Gupta, Ananya
The Himalaya-Hindu Kush mountain range and the Tibetan Plateau birth ten of Asia’s most prominent rivers providing irrigation, energy, and drinking water to over two billion people across several countries today. Therefore, transboundary water shar
Autor:
Pineda, Elisa, Atanasova, Petya, Wellappuli, Nalinda Tharanga, Kusuma, Dian, Herath, Himali, Segal, Alexa Blair, Vandevijvere, Stefanie, Anjana, Ranjit Mohan, Shamim, Abu Ahmed, Afzal, Saira, Akter, Fahmida, Aziz, Faiza, Gupta, Ananya, Hanif, Abu Abdullah, Hasan, Mehedi, Jayatissa, Renuka, Jha, Sujeet, Jha, Vinitaa, Katulanda, Prasad, Khawaja, Khadija Irfan, Kumarendran, Balachandran, Loomba, Menka, Mahmood, Sara, Mridha, Malay Kanthi, Pradeepa, Rajendra, Aarthi, Garudam Raveendiran, Tyagi, Akansha, Kasturiratne, Anuradhani, Sassi, Franco, Miraldo, Marisa
Publikováno v:
In The Lancet Regional Health - Southeast Asia July 2024 26
Publikováno v:
Proceedings of International Conference on Artificial Neural Networks , 2019. pg-669-684
Timely disaster risk management requires accurate road maps and prompt damage assessment. Currently, this is done by volunteers manually marking satellite imagery of affected areas but this process is slow and often error-prone. Segmentation algorith
Externí odkaz:
http://arxiv.org/abs/2006.05589
Satellite images are an extremely valuable resource in the aftermath of natural disasters such as hurricanes and tsunamis where they can be used for risk assessment and disaster management. In order to provide timely and actionable information for di
Externí odkaz:
http://arxiv.org/abs/2006.05575
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 2, pp. 971-981, Feb. 2020
LiDAR provides highly accurate 3D point clouds. However, data needs to be manually labelled in order to provide subsequent useful information. Manual annotation of such data is time consuming, tedious and error prone, and hence in this paper we prese
Externí odkaz:
http://arxiv.org/abs/2006.05560
Explainability is an important factor to drive user trust in the use of neural networks for tasks with material impact. However, most of the work done in this area focuses on image analysis and does not take into account 3D data. We extend the salien
Externí odkaz:
http://arxiv.org/abs/2006.05548
A semantic feature extraction method for multitemporal high resolution aerial image registration is proposed in this paper. These features encode properties or information about temporally invariant objects such as roads and help deal with issues suc
Externí odkaz:
http://arxiv.org/abs/1908.11822