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pro vyhledávání: '"Mohsenin A"'
Autor:
Rashid, Hasib-Al, Mohsenin, Tinoosh
The advancement of sophisticated artificial intelligence (AI) algorithms has led to a notable increase in energy usage and carbon dioxide emissions, intensifying concerns about climate change. This growing problem has brought the environmental sustai
Externí odkaz:
http://arxiv.org/abs/2405.12353
Autor:
Rashid, Hasib-Al, Sarkar, Argho, Gangopadhyay, Aryya, Rahnemoonfar, Maryam, Mohsenin, Tinoosh
Traditional machine learning models often require powerful hardware, making them unsuitable for deployment on resource-limited devices. Tiny Machine Learning (tinyML) has emerged as a promising approach for running machine learning models on these de
Externí odkaz:
http://arxiv.org/abs/2404.03574
Demand for efficient onboard object detection is increasing due to its key role in autonomous navigation. However, deploying object detection models such as YOLO on resource constrained edge devices is challenging due to the high computational requir
Externí odkaz:
http://arxiv.org/abs/2312.11716
Solving long-horizon, temporally-extended tasks using Reinforcement Learning (RL) is challenging, compounded by the common practice of learning without prior knowledge (or tabula rasa learning). Humans can generate and execute plans with temporally-e
Externí odkaz:
http://arxiv.org/abs/2311.05596
Robots have been successfully used to perform tasks with high precision. In real-world environments with sparse rewards and multiple goals, learning is still a major challenge and Reinforcement Learning (RL) algorithms fail to learn good policies. Tr
Externí odkaz:
http://arxiv.org/abs/2308.08737
Publikováno v:
Clinical Ophthalmology, Vol 2013, Iss default, Pp 787-792 (2013)
Amir Mohsenin,1 Vahid Mohsenin,2 Ron A Adelman1 1Department of Ophthalmology and Visual Science, Yale University School of Medicine, New Haven, Connecticut, USA; 2Yale Center for Sleep Medicine, Department of Medicine, Yale University School of Medic
Externí odkaz:
https://doaj.org/article/770c734888d6456fa983929bd680a835
Explainability of neural network prediction is essential to understand feature importance and gain interpretable insight into neural network performance. However, explanations of neural network outcomes are mostly limited to visualization, and there
Externí odkaz:
http://arxiv.org/abs/2211.01413
Learning to solve long horizon temporally extended tasks with reinforcement learning has been a challenge for several years now. We believe that it is important to leverage both the hierarchical structure of complex tasks and to use expert supervisio
Externí odkaz:
http://arxiv.org/abs/2210.08412
Publikováno v:
Clinical Ophthalmology, Vol 2012, Iss default, Pp 2045-2047 (2012)
Amir Mohsenin,1 John Sinard,1,2 John J Huang11Department of Ophthalmology and Visual Science, 2Department of Pathology, Yale University School of Medicine, New Haven, CT, USAAbstract: This report describes a unique case of coexisting necrobiotic xant
Externí odkaz:
https://doaj.org/article/9cb17ee1b9e44069b59df91cea43727c
TinyM$^2$Net: A Flexible System Algorithm Co-designed Multimodal Learning Framework for Tiny Devices
With the emergence of Artificial Intelligence (AI), new attention has been given to implement AI algorithms on resource constrained tiny devices to expand the application domain of IoT. Multimodal Learning has recently become very popular with the cl
Externí odkaz:
http://arxiv.org/abs/2202.04303