Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Anirudh Som"'
Publikováno v:
Frontiers in Computer Science, Vol 3 (2021)
Early development of specific skills can help students succeed in fields like Science, Technology, Engineering and Mathematics. Different education standards consider “Collaboration” as a required and necessary skill that can help students excel
Externí odkaz:
https://doaj.org/article/ca226701d97b4a7da72f383f024eadcd
Autor:
Vijay K. Somani, MD, Ashwini Annabathula, MD, Anirudh Somani, MD, Indukooru S. Reddy, MD, DNB
Publikováno v:
JAAD Case Reports, Vol 53, Iss , Pp 116-118 (2024)
Externí odkaz:
https://doaj.org/article/2487e11a34fb48b5aaface16a05cafde
Publikováno v:
Ankita Shukla
Deep neural networks have increasingly been used as an auxiliary tool in healthcare applications, due to their ability to improve performance of several diagnosis tasks. However, these methods are not widely adopted in clinical settings due to the pr
Publikováno v:
IEEE Internet Things J
Deep neural networks are parametrized by several thousands or millions of parameters, and have shown tremendous success in many classification problems. However, the large number of parameters makes it difficult to integrate these models into edge de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d0cd726c3baf6be512481d1cf814475
Publikováno v:
Annu Int Conf IEEE Eng Med Biol Soc
EMBC
EMBC
Application and use of deep learning algorithms for different healthcare applications is gaining interest at a steady pace. However, use of such algorithms can prove to be challenging as they require large amounts of training data that capture differ
Publikováno v:
EMBC
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together with machi
Publikováno v:
CVPR Workshops
Deep-learning architectures for classification problems involve the cross-entropy loss sometimes assisted with auxiliary loss functions like center loss, contrastive loss and triplet loss. These auxiliary loss functions facilitate better discriminati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c6fe3c365c7ff8409ca5e3560f36f18
http://arxiv.org/abs/2004.09805
http://arxiv.org/abs/2004.09805
Publikováno v:
Computer Vision – ECCV 2020 Workshops ISBN: 9783030654139
ECCV Workshops (6)
ECCV Workshops (6)
K-12 classrooms consistently integrate collaboration as part of their learning experiences. However, owing to large classroom sizes, teachers do not have the time to properly assess each student and give them feedback. In this paper we propose using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b4a2f8b761bcac44aabd8b4a4a28a1e
https://doi.org/10.1007/978-3-030-65414-6_8
https://doi.org/10.1007/978-3-030-65414-6_8
Publikováno v:
Handbook of Variational Methods for Nonlinear Geometric Data ISBN: 9783030313500
In this chapter, we present an overview of recent techniques from the emerging area of topological data analysis (TDA), with a focus on machine-learning applications. TDA methods are concerned with measuring shape-related properties of point-clouds a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::273e3511af980c09eb58ed9b2407a944
https://doi.org/10.1007/978-3-030-31351-7_15
https://doi.org/10.1007/978-3-030-31351-7_15
Publikováno v:
Conf Comput Vis Pattern Recognit Workshops
CVPR Workshops
CVPR Workshops
Topological features such as persistence diagrams and their functional approximations like persistence images (PIs) have been showing substantial promise for machine learning and computer vision applications. This is greatly attributed to the robustn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dbfef24ea3d727f633ebcfcc958fb88b
http://arxiv.org/abs/1906.01769
http://arxiv.org/abs/1906.01769