Zobrazeno 1 - 10
of 457
pro vyhledávání: '"SINGH, ASHEESH"'
Autor:
Kim, Bitgoeul, Blair, Samuel W., Jubery, Talukder Z., Sarkar, Soumik, Singh, Arti, Singh, Asheesh K., Ganapathysubramanian, Baskar
Plant breeding programs require assessments of days to maturity for accurate selection and placement of entries in appropriate tests. In the early stages of the breeding pipeline, soybean breeding programs assign relative maturity ratings to experime
Externí odkaz:
http://arxiv.org/abs/2412.09696
Autor:
Feng, Jiale, Blair, Samuel W., Ayanlade, Timilehin, Balu, Aditya, Ganapathysubramanian, Baskar, Singh, Arti, Sarkar, Soumik, Singh, Asheesh K
We present a novel method for soybean (Glycine max (L.) Merr.) yield estimation leveraging high throughput seed counting via computer vision and deep learning techniques. Traditional methods for collecting yield data are labor-intensive, costly, pron
Externí odkaz:
http://arxiv.org/abs/2412.02642
Autor:
Khosravi, Mahsa, Carroll, Matthew, Tan, Kai Liang, Van der Laan, Liza, Raigne, Joscif, Mueller, Daren S., Singh, Arti, Balu, Aditya, Ganapathysubramanian, Baskar, Singh, Asheesh Kumar, Sarkar, Soumik
Agricultural production requires careful management of inputs such as fungicides, insecticides, and herbicides to ensure a successful crop that is high-yielding, profitable, and of superior seed quality. Current state-of-the-art field crop management
Externí odkaz:
http://arxiv.org/abs/2409.00735
Autor:
Arshad, Muhammad Arbab, Jubery, Talukder Zaki, Roy, Tirtho, Nassiri, Rim, Singh, Asheesh K., Singh, Arti, Hegde, Chinmay, Ganapathysubramanian, Baskar, Balu, Aditya, Krishnamurthy, Adarsh, Sarkar, Soumik
Plant stress phenotyping traditionally relies on expert assessments and specialized models, limiting scalability in agriculture. Recent advances in multimodal large language models (LLMs) offer potential solutions to this challenge. We present AgEval
Externí odkaz:
http://arxiv.org/abs/2407.19617
Autor:
Yang, Chih-Hsuan, Feuer, Benjamin, Jubery, Zaki, Deng, Zi K., Nakkab, Andre, Hasan, Md Zahid, Chiranjeevi, Shivani, Marshall, Kelly, Baishnab, Nirmal, Singh, Asheesh K, Singh, Arti, Sarkar, Soumik, Merchant, Nirav, Hegde, Chinmay, Ganapathysubramanian, Baskar
We introduce Arboretum, the largest publicly accessible dataset designed to advance AI for biodiversity applications. This dataset, curated from the iNaturalist community science platform and vetted by domain experts to ensure accuracy, includes 134.
Externí odkaz:
http://arxiv.org/abs/2406.17720
Autor:
Saleem, Nasla, Balu, Aditya, Jubery, Talukder Zaki, Singh, Arti, Singh, Asheesh K., Sarkar, Soumik, Ganapathysubramanian, Baskar
Data augmentation is a powerful tool for improving deep learning-based image classifiers for plant stress identification and classification. However, selecting an effective set of augmentations from a large pool of candidates remains a key challenge,
Externí odkaz:
http://arxiv.org/abs/2406.13081
Autor:
Jones, Sarah E., Ayanlade, Timilehin, Fallen, Benjamin, Jubery, Talukder Z., Singh, Arti, Ganapathysubramanian, Baskar, Sarkar, Soumik, Singh, Asheesh K.
Soybean production is susceptible to biotic and abiotic stresses, exacerbated by extreme weather events. Water limiting stress, i.e. drought, emerges as a significant risk for soybean production, underscoring the need for advancements in stress monit
Externí odkaz:
http://arxiv.org/abs/2402.18751
Autor:
Balabaygloo, Behzad J., Bekee, Barituka, Blair, Samuel W., Fey, Suzanne, Fotouhi, Fateme, Gupta, Ashish, Menke, Kevin, Vangala, Anusha, Palomares, Jorge C. M., Prestholt, Aaron, Tanwar, Vishesh K., Tao, Xu, Carroll, Matthew E., Das, Sajal, Depaula, Gil, Kyveryga, Peter, Sarkar, Soumik, Segovia, Michelle, Sylvestri, Simone, Valdivia, Corinne, Singh, Asheesh K.
To meet the grand challenges of agricultural production including climate change impacts on crop production, a tight integration of social science, technology and agriculture experts including farmers are needed. There are rapid advances in informati
Externí odkaz:
http://arxiv.org/abs/2312.12338
Autor:
Gupta, Aditya, Singh, Asheesh
Agriculture, as the cornerstone of human civilization, constantly seeks to integrate technology for enhanced productivity and sustainability. This paper introduces $\textit{Agri-GNN}$, a novel Genotypic-Topological Graph Neural Network Framework tail
Externí odkaz:
http://arxiv.org/abs/2310.13037
Autor:
Chiranjeevi, Shivani, Sadaati, Mojdeh, Deng, Zi K, Koushik, Jayanth, Jubery, Talukder Z, Mueller, Daren, Neal, Matthew E O, Merchant, Nirav, Singh, Aarti, Singh, Asheesh K, Sarkar, Soumik, Singh, Arti, Ganapathysubramanian, Baskar
Insect-pests significantly impact global agricultural productivity and quality. Effective management involves identifying the full insect community, including beneficial insects and harmful pests, to develop and implement integrated pest management s
Externí odkaz:
http://arxiv.org/abs/2306.02507