Search Results - "Pargi, Mohan Kashyap"

Theory‐Guided Machine Learning to Predict the Performance of Noble Metal Catalysts in the Water‐Gas Shift Reaction by Chattoraj, Joyjit, Hamadicharef, Brahim, Kong, Jian Feng, Pargi, Mohan Kashyap, Zeng, Yingzhi, Poh, Chee Kok, Chen, Luwei, Gao, Fei, Tan, Teck Leong

“…Machine learning (ML) has widespread applications in catalyst discovery and reaction optimization. We present a theory‐guided machine learning framework to…”
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Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study by Yang, Lily Wei Yun, Ng, Wei Yan, Lei, Xiaofeng, Tan, Shaun Chern Yuan, Wang, Zhaoran, Yan, Ming, Pargi, Mohan Kashyap, Zhang, Xiaoman, Lim, Jane Sujuan, Gunasekeran, Dinesh Visva, Tan, Franklin Chee Ping, Lee, Chen Ee, Yeo, Khung Keong, Tan, Hiang Khoon, Ho, Henry Sun Sien, Tan, Benedict Wee Bor, Wong, Tien Yin, Kwek, Kenneth Yung Chiang, Goh, Rick Siow Mong, Liu, Yong, Ting, Daniel Shu Wei

“…The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there…”
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Improving Aquaculture Systems using AI: Employing predictive models for Biomass Estimation on Sonar Images by Pargi, Mohan Kashyap, Bagheri, Elham, F, Ricardo Shirota, Eng Huat, Khoo, Shishehchian, Farshad, Nathalie, Nathalie

“…Accurate biomass estimation is a major concern in the aquaculture industry due to its role in the efficient operations of fish farms. In this paper, we propose…”
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Cover Feature: Theory‐Guided Machine Learning to Predict the Performance of Noble Metal Catalysts in the Water‐Gas Shift Reaction (ChemCatChem 16/2022) by Chattoraj, Joyjit, Hamadicharef, Brahim, Kong, Jian Feng, Pargi, Mohan Kashyap, Zeng, Yingzhi, Poh, Chee Kok, Chen, Luwei, Gao, Fei, Tan, Teck Leong

“…The Cover Feature illustrates a theory‐guided machine learning framework for water‐gas shift reaction optimization. In their Research Article, J. Chattoraj, T…”
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Classification of different vehicles in traffic using RGB and Depth images: A Fast RCNN Approach by Pargi, Mohan Kashyap, Setiawan, Bondan, Kazama, Yoriko

“…The Fast RCNN framework utilizes the region proposals generated from the RGB images in general for object classification and detection. This paper describes…”
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