Ag-IoT for crop and environment monitoring: Past, present, and future

N Chamara, MD Islam, GF Bai, Y Shi, P Song, J Wang, X Guo, W Yang, C Zhao - The Crop Journal, 2021 - Elsevier
With the rapid development of genetic analysis techniques and crop population size,
phenoty** has become the bottleneck restricting crop breeding. Breaking through this …

Deep learning for plant stress phenoty**: trends and future perspectives

AK Singh, B Ganapathysubramanian, S Sarkar… - Trends in plant …, 2018 - cell.com
Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile
tool to assimilate large amounts of heterogeneous data and provide reliable predictions of …

A research review on deep learning combined with hyperspectral Imaging in multiscale agricultural sensing

L Shuai, Z Li, Z Chen, D Luo, J Mu - Computers and Electronics in …, 2024 - Elsevier
Efficient and automated data acquisition techniques, as well as intelligent and accurate data
processing and analysis techniques, are essential for the advancement of precision …

A review of deep learning applications for genomic selection

OA Montesinos-López, A Montesinos-López… - BMC genomics, 2021 - Springer
Abstract Background Several conventional genomic Bayesian (or no Bayesian) prediction
methods have been proposed including the standard additive genetic effect model for which …

[HTML][HTML] A review of imaging techniques for plant disease detection

V Singh, N Sharma, S Singh - Artificial Intelligence in Agriculture, 2020 - Elsevier
Agriculture is the basis of every economy worldwide. Crop production is one of the major
factors affecting domestic market condition in any country. Agricultural production is also a …

MobileNet based apple leaf diseases identification

C Bi, J Wang, Y Duan, B Fu, JR Kang, Y Shi - Mobile Networks and …, 2022 - Springer
Alternaria leaf blotch, and rust are two common types of apple leaf diseases that severely
affect apple yield. A timely and effective detection of apple leaf diseases is crucial for …