SpikeSegNet-a deep learning approach utilizing encoder-decoder network with hourglass for spike segmentation and counting in wheat plant from visual imaging T Misra, A Arora, S Marwaha, V Chinnusamy, AR Rao, R Jain, RN Sahoo, ... Plant methods 16, 1-20, 2020 | 92 | 2020 |
Web-SpikeSegNet: deep learning framework for recognition and counting of spikes from visual images of wheat plants T Misra, A Arora, S Marwaha, RR Jha, M Ray, R Jain, AR Rao, ... IEEE Access 9, 76235-76247, 2021 | 22 | 2021 |
A lightweight convolutional neural network for recognition of severity stages of maydis leaf blight disease of maize MA Haque, S Marwaha, A Arora, CK Deb, T Misra, S Nigam, KS Hooda Frontiers in Plant Science 13, 1077568, 2022 | 9 | 2022 |
Artificial neural network for estimating leaf fresh weight of rice plant through visual-nir imaging T Misra, A Arora, S Marwaha, M Ray, D Raju, S Kumar, S Goel, RN Sahoo, ... Indian J. Agric. Sci 89, 1698-1702, 2019 | 8 | 2019 |
Web enabled and weather based forewarning of yellow stem borer [Scirpophaga incertulas (Walker)] and leaf folder [Cnaphalocrcis medinalis (Guenee)] for different rice growing … A Kumar, T Misra, K Batra, R Sharma, AK Mishra, S Vennila, RK Tanwar, ... Mausam 67 (4), 861-868, 2016 | 5 | 2016 |
Circular bioeconomy in agricultural food supply chain and value addition A Kumar, VDC Baskar, U Malaiarasan, T Misra, M Dobriyal, A Kumar Biomass, Biofuels, Biochemicals, 109-122, 2022 | 4 | 2022 |
Yield-SpikeSegNet: An Extension of SpikeSegNet Deep-Learning Approach for the Yield Estimation in the Wheat Using Visual Images SKVC Tanuj Misra, Alka Arora, Sudeep Marwaha, Ranjeet Ranjan Jha, Mrinmoy ... Applied Artificial Intelligence 36 (1), e2137642 (3302 pages), 2022 | 3 | 2022 |
Leaf area assessment using image processing and support vector regression in rice T Misra, S Marwaha, A Arora, M Ray, S Kumar, S Kumar Indian Journal of Agricultural Sciences 91 (3), 388–92, 2020 | 2 | 2020 |
A comparative study of chlorophyll content estimation techniques through image analysis. T Misra, S Priyadarshini, A Arora, S Marwaha, HS Roy, M Ray | 2 | 2018 |
Computer Vision Approaches for Plant Phenotypic Parameter Determination A Arora, T Misra, M Kumar, S Marwaha, S Kumar, V Chinnusamy Digital Ecosystem for Innovation in Agriculture, 263-270, 2023 | 1 | 2023 |
High-Throughput Phenomics of Crops for Water and Nitrogen Stress RN Sahoo, C Viswanathan, M Kumar, S Bhugra, S Karwa, T Misra, ... Translating Physiological Tools to Augment Crop Breeding, 291-310, 2023 | 1 | 2023 |
Computer-Vision-Ansätze zur Bestimmung phänotypischer Parameter von Pflanzen V Arora, A., Misra, T., Kumar, M., Marwaha, S., Kumar, S., Chinnusamy Digitales Ökosystem für Innovationen in der Landwirtschaft., 289–297, 2024 | | 2024 |
R Package: 'biologicalActivityIndices'. Title: "Biological Activity Indices" - Version 0.1.0 SS Avijit Ghosh, Tanuj Misra, Amit Kumar Singh, Arun Shukla CRAN, 2024 | | 2024 |
Package ‘FWRGB’ T Misra, A Arora, S Marwaha, S Kumar, M Ray | | 2021 |
Image Analysis Algorithms for High-throughput Phenotyping of Rice and Wheat M TANUJ ICAR-Indian Agricultural Statistics Research Institute ICAR-Indian …, 2019 | | 2019 |
Online software for forewarning of onion thrips S Chandra, A Arora, A Kumar, R Jain, S Marwaha, T Misra 2016 3rd International Conference on Computing for Sustainable Global …, 2016 | | 2016 |
NON-DESTRUCTIVE PHENOTYPING OF RICE PLANT THROUGH IMAGE ANALYSIS M TANUJ IARI, INDIAN AGRICULTURAL STATISTICS RESEARCH INSTITUTE, NEW DELHI, 2013 | | 2013 |