Machine learning and deep learning based computational techniques in automatic agricultural diseases detection: Methodologies, applications, and challenges
Plant disease detection is a critical issue that needs to be focused on for productive
agriculture and economy. Detecting plant disease using traditional methods is a tedious job …
agriculture and economy. Detecting plant disease using traditional methods is a tedious job …
A systematic review of citrus disease perceptions and fruit grading using machine vision
Citrus is one of the most commonly farmed and popular fruit crops globally. Citrus fruits are
high in vitamins, minerals, and dietary fibre, which are essential for overall health. Oranges …
high in vitamins, minerals, and dietary fibre, which are essential for overall health. Oranges …
Diagnosis and recognition of grape leaf diseases: An automated system based on a novel saliency approach and canonical correlation analysis based multiple …
Efficient and fast segmentation of fruit symptoms is one of the major businesses nowadays in
the agro-economy. Manual segmentation and recognition of fruit symptoms is a hard job …
the agro-economy. Manual segmentation and recognition of fruit symptoms is a hard job …
[PDF][PDF] Deep Learning-Based Trees Disease Recognition and Classification Using Hyperspectral Data.
Crop diseases have a significant impact on plant growth and can lead to reduced yields.
Traditional methods of disease detection rely on the expertise of plant protection experts …
Traditional methods of disease detection rely on the expertise of plant protection experts …
Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations
Accurate and rapid plant disease detection is critical for enhancing long-term agricultural
yield. Disease infection poses the most significant challenge in crop production, potentially …
yield. Disease infection poses the most significant challenge in crop production, potentially …
Hybridized approach of image segmentation in classification of fruit mango using BPNN and discriminant analyzer
N Kumari, A Kr. Bhatt, R Kr. Dwivedi… - Multimedia Tools and …, 2021 - Springer
In machine learning, image classification accuracy generally depends on image
segmentation and feature extraction methods with the extracted features and its qualities …
segmentation and feature extraction methods with the extracted features and its qualities …
Convolutional neural networks for image-based corn kernel detection and counting
Precise in-season corn grain yield estimates enable farmers to make real-time accurate
harvest and grain marketing decisions minimizing possible losses of profitability. A well …
harvest and grain marketing decisions minimizing possible losses of profitability. A well …
Plant disease identification and detection using support vector machines and artificial neural networks
In growing nations like India, agriculture plays a vital role in the economy. Increase in agro-
products affects the GDP of the nation to a good extent. To increase the productivity in …
products affects the GDP of the nation to a good extent. To increase the productivity in …
A cognitive memory-augmented network for visual anomaly detection
With the rapid development of automated visual analysis, visual analysis systems have
become a popular research topic in the field of computer vision and automated analysis …
become a popular research topic in the field of computer vision and automated analysis …
Date palm disease identification using features extraction and deep learning approach
The world is advancing in various fields of life, computers are intervening in every task
progressively. In this context, biotechnology software applications are on the peak to solve …
progressively. In this context, biotechnology software applications are on the peak to solve …