%0 Journal Article %1 noauthororeditor %A Rajest, S. Suman %D 2023 %J CENTRAL ASIAN JOURNAL OF THEORETICAL AND APPLIED SCIENCE %K Agricultural CNN Deep Detection, Disease Learning, Output, %N 3 %P 67-91 %T The Use of Deep Learning Methods for the Detection of Diseases in Plant Leaves %U https://cajotas.centralasianstudies.org/index.php/CAJOTAS/article/view/1122/1146 %V 4 %X Leaf diseases on plants pose a significant risk to global food security because they significantly lower crop yield and quality. It has proven difficult to diagnose diseases in a way that is both accurate and precise. The recent advancements in computer vision have made it possible and opened the door for disease diagnosis of plant leaves using a camera-assisted deep learning approach. This was previously impossible. An intelligent disease diagnosis system is a forward-thinking piece of technology that contributes to the enhancement of both the quality and quantity of agricultural output in the nation. Therefore, the efficient disease detection convolution neural networks (CNN) model is applied in order to categorise the diseases that are present on the provided leaf based on the image dataset. Therefore, it has come to our attention that neural networks are able to capture the colours and qualities of lesions that are distinctive to certain diseases.

@article{noauthororeditor, abstract = {Leaf diseases on plants pose a significant risk to global food security because they significantly lower crop yield and quality. It has proven difficult to diagnose diseases in a way that is both accurate and precise. The recent advancements in computer vision have made it possible and opened the door for disease diagnosis of plant leaves using a camera-assisted deep learning approach. This was previously impossible. An intelligent disease diagnosis system is a forward-thinking piece of technology that contributes to the enhancement of both the quality and quantity of agricultural output in the nation. Therefore, the efficient disease detection convolution neural networks (CNN) model is applied in order to categorise the diseases that are present on the provided leaf based on the image dataset. Therefore, it has come to our attention that neural networks are able to capture the colours and qualities of lesions that are distinctive to certain diseases.}, added-at = {2023-08-22T11:41:50.000+0200}, author = {Rajest, S. Suman}, biburl = {https://www.bibsonomy.org/bibtex/262aa276ba7113d5ac998dfa7f0581199/centralasian_20}, interhash = {86edeb2ea5cad65bb1fad567d7f98752}, intrahash = {62aa276ba7113d5ac998dfa7f0581199}, issn = {2660-5317}, journal = {CENTRAL ASIAN JOURNAL OF THEORETICAL AND APPLIED SCIENCE}, keywords = {Agricultural CNN Deep Detection, Disease Learning, Output,}, language = {english}, month = {march}, number = 3, pages = {67-91}, timestamp = {2023-08-22T11:41:50.000+0200}, title = {The Use of Deep Learning Methods for the Detection of Diseases in Plant Leaves}, url = {https://cajotas.centralasianstudies.org/index.php/CAJOTAS/article/view/1122/1146}, volume = 4, year = 2023 }