Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming
The digitalization of data has resulted in a data tsunami in practically every industry of data-
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …
Review on convolutional neural network (CNN) applied to plant leaf disease classification
J Lu, L Tan, H Jiang - Agriculture, 2021 - mdpi.com
Crop production can be greatly reduced due to various diseases, which seriously endangers
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …
Machine learning applications for precision agriculture: A comprehensive review
Agriculture plays a vital role in the economic growth of any country. With the increase of
population, frequent changes in climatic conditions and limited resources, it becomes a …
population, frequent changes in climatic conditions and limited resources, it becomes a …
Identification of plant-leaf diseases using CNN and transfer-learning approach
The timely identification and early prevention of crop diseases are essential for improving
production. In this paper, deep convolutional-neural-network (CNN) models are …
production. In this paper, deep convolutional-neural-network (CNN) models are …
Agricultural plant diseases identification: From traditional approach to deep learning
Plant disease computerization in agriculture areas an important for every country, as the
population rate increases the demand for food supply also increases. Today, the significant …
population rate increases the demand for food supply also increases. Today, the significant …
A survey of deep convolutional neural networks applied for prediction of plant leaf diseases
In the modern era, deep learning techniques have emerged as powerful tools in image
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …
Technological revolutions in smart farming: Current trends, challenges & future directions
With increasing population, the demand for agricultural productivity is rising to meet the goal
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …
A review of deep learning techniques used in agriculture
Deep learning (DL) is a robust data-analysis and image-processing technique that has
shown great promise in the agricultural sector. In this study, 129 papers that are based on …
shown great promise in the agricultural sector. In this study, 129 papers that are based on …
Plant disease detection and classification by deep learning
Plant diseases affect the growth of their respective species, therefore their early identification
is very important. Many Machine Learning (ML) models have been employed for the …
is very important. Many Machine Learning (ML) models have been employed for the …
Remote sensing in agriculture—accomplishments, limitations, and opportunities
Remote sensing (RS) technologies provide a diagnostic tool that can serve as an early
warning system, allowing the agricultural community to intervene early on to counter …
warning system, allowing the agricultural community to intervene early on to counter …