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Badri Narayanan
Badri Narayanan
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Extracting pasture phenotype and biomass percentages using weakly supervised multi-target deep learning on a small dataset
B Narayanan, M Saadeldin, P Albert, K McGuinness, B Mac Namee
arXiv preprint arXiv:2101.03198, 2021
152021
Semi-supervised dry herbage mass estimation using automatic data and synthetic images
P Albert, M Saadeldin, B Narayanan, B Mac Namee, D Hennessy, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
82021
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation
P Albert, M Saadeldin, B Narayanan, B Mac Namee, D Hennessy, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
62022
Using image analysis and machine learning to estimate sward clover content
D Hennessy, M Saadeldin, B Mac Namee, NE O'Connor, K McGuinness, ...
21st Symposium of the European Grassland Federation 26 (Grassland Science in …, 2021
22021
Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation
P Albert, M Saadeldin, B Narayanan, B Mac Namee, D Hennessy, ...
arXiv preprint arXiv:2204.09343, 2022
12022
Adaptation of Compositional Data Analysis in Deep Learning to Predict Pasture Biomass Proportions.
B Narayanan, M Saadeldin, P Albert, K McGuinness, NE O'Connor, ...
AICS, 176-187, 2021
2021
An Unsupervised Hierarchical Attention Neural Network for Topic Extraction of Support Ticket
A Kumar, A Nabhan, B Jensen, A Basak, P Mandlecha, M Chintalapati, ...
2018
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