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pro vyhledávání: '"Devshali, Charu Chandra"'
Autor:
Sani, Depanshu, Mahato, Sandeep, Saini, Sourabh, Agarwal, Harsh Kumar, Devshali, Charu Chandra, Anand, Saket, Arora, Gaurav, Jayaraman, Thiagarajan
The availability of well-curated datasets has driven the success of Machine Learning (ML) models. Despite greater access to earth observation data in agriculture, there is a scarcity of curated and labelled datasets, which limits the potential of its
Externí odkaz:
http://arxiv.org/abs/2312.00069
Autor:
Sani, Depanshu, Mahato, Sandeep, Sirohi, Parichya, Anand, Saket, Arora, Gaurav, Devshali, Charu Chandra, Jayaraman, Thiagarajan, Agarwal, Harsh Kumar
The availability of well-curated datasets has driven the success of Machine Learning (ML) models. Despite the increased access to earth observation data for agriculture, there is a scarcity of curated, labelled datasets, which limits the potential of
Externí odkaz:
http://arxiv.org/abs/2209.12238
Autor:
Sani, Depanshu, Mahato, Sandeep, Sirohi, Parichya, Anand, Saket, Arora, Gaurav, Devshali, Charu Chandra, Jayaraman, T.
The integration of the modern Machine Learning (ML) models into remote sensing and agriculture has expanded the scope of the application of satellite images in the agriculture domain. In this paper, we present how the accuracy of crop type identifica
Externí odkaz:
http://arxiv.org/abs/2205.03104