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HAR-Depth: A Novel Framework for Human Action Recognition Using Sequential Learning and Depth Estimated History Images
This is the Accepted Manuscript version of an article that proposes HAR-Depth with sequential and shape learning along with the novel concept of depth history image (DHI) to address the challenges of Human action recognition (HAR). Results suggest that the proposed work of this paper performs better in terms of overall accuracy, kappa parameter and precision compared to the other state-of-the-art algorithms present in the earlier reported literature.
Date:
August 24, 2020
Creator:
Sahoo, Suraj Prakash; Ari, Samit; Mahapatra, Kamalakanta & Mohanty, Saraju P.
System:
The UNT Digital Library
sCrop: A Novel Device for Sustainable Automatic Disease Prediction, Crop Selection, and Irrigation in Internet-of-Agro-Things for Smart Agriculture
Accepted Manuscript version of an article introducing the innovative idea of the Internet-of-Agro-Things (IoAT) with an explanation of the automatic detection of plant disease for the development of Agriculture Cyber-Physical System (ACPS). An accuracy of 99.24% is achieved by the proposed plant disease prediction framework.
Date:
August 15, 2021
Creator:
Udutalapally, Venkanna; Mohanty, Saraju P.; Pallagani, Vishal & Khandelwal, Vedant
System:
The UNT Digital Library