35 citations · 43 across the 3 of their papers we have counts for
4 papers
Usefulness of interpretability methods to explain deep learning based plant stress phenotyping
Koushik Nagasubramanian, Asheesh K. Singh, Arti Singh +2
Deep learning techniques have been successfully deployed for automating plant stress identification and quantification. In recent years, there is a growing push towards training mo…
How useful is Active Learning for Image-based Plant Phenotyping?
Koushik Nagasubramanian, Talukder Z. Jubery, Fateme Fotouhi Ardakani +5
Deep learning models have been successfully deployed for a diverse array of image-based plant phenotyping applications including disease detection and classification. However, succ…
Explaining hyperspectral imaging based plant disease identification: 3D CNN and saliency maps
Koushik Nagasubramanian, Sarah Jones, Asheesh K. Singh +3
Our overarching goal is to develop an accurate and explainable model for plant disease identification using hyperspectral data. Charcoal rot is a soil borne fungal disease that aff…
Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean
Koushik Nagasubramanian, Sarah Jones, Soumik Sarkar +3
Charcoal rot is a fungal disease that thrives in warm dry conditions and affects the yield of soybeans and other important agronomic crops worldwide. There is a need for robust, au…