R Manavalan - Computers and Electronics in Agriculture, 2020 - Elsevier
Agricultural productivity significantly contributes to every country's economy. The grain plants such as wheat, rice, corn (maize), barley, oats, rye, millet, and sorghum are commonly …
S Kaur, S Pandey, S Goel - Archives of Computational Methods in …, 2019 - Springer
The symptoms of plant diseases are evident in different parts of a plant; however leaves are found to be the most commonly observed part for detecting an infection. Researchers have …
Agriculture has been the most primary source of the livelihood of man for thousands of years. Even today, it provides subsistence to about 50% of the world population. Plant …
Y Sun, Z Jiang, L Zhang, W Dong, Y Rao - Computers and electronics in …, 2019 - Elsevier
For the purpose of improving the extraction of tea plant leaf disease saliency map under complex backgrounds, a new algorithm combining SLIC (Simple Linear Iterative Cluster) …
M Das, A Bais - IEEE access, 2021 - ieeexplore.ieee.org
Farmers around the world face the challenge of growing more food for the increasing world population. On top of that, external threats such as pests (weeds and insects) pose a threat …
X Zuo, J Chu, J Shen, J Sun - Agriculture, 2022 - mdpi.com
Combining disease categories and crop species leads to complex intra-class and inter-class differences. Significant intra-class difference and subtle inter-class difference pose a great …
Accurate identification of plant diseases caused by several pathogens likes fungi, bacteria and viruses, etc. and disorders due to mineral deficiency at field level are a serious problem …
E Dhinesh, A Jagan - 2019 11th International Conference on …, 2019 - ieeexplore.ieee.org
Agriculturalists find difficulties in classifying the diseases in leaves. In olden days, farmers detected the leaf diseases by observing the leaf by its appearance which does not provide …