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 …
DeepThink IoT: the strength of deep learning in internet of things
Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …
revolutionized technology in the twenty-first century, enabling humans and machines to …
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 …
affect apple yield. A timely and effective detection of apple leaf diseases is crucial for …
Citrus disease detection and classification using end-to-end anchor-based deep learning model
Plant diseases are the primary issue that reduces agricultural yield and production, causing
significant economic losses and instability in the food supply. In plants, citrus is a fruit crop of …
significant economic losses and instability in the food supply. In plants, citrus is a fruit crop of …
Internet of Things (IoT) and machine learning model of plant disease prediction–blister blight for tea plant
Crop plant diseases are a significant threat to productivity and sustainable development in
agriculture. Early prediction of disease attacks is useful for the effective control of the …
agriculture. Early prediction of disease attacks is useful for the effective control of the …
Classification of olive leaf diseases using deep convolutional neural networks
S Uğuz, N Uysal - Neural computing and applications, 2021 - Springer
In recent years, there have been significant achievements in object classification with
various techniques using several deep learning architectures. These architectures are now …
various techniques using several deep learning architectures. These architectures are now …
Predicting plant growth from time-series data using deep learning
Phenotyping involves the quantitative assessment of the anatomical, biochemical, and
physiological plant traits. Natural plant growth cycles can be extremely slow, hindering the …
physiological plant traits. Natural plant growth cycles can be extremely slow, hindering the …
Computer vision with deep learning for plant phenotyping in agriculture: A survey
In light of growing challenges in agriculture with ever growing food demand across the
world, efficient crop management techniques are necessary to increase crop yield. Precision …
world, efficient crop management techniques are necessary to increase crop yield. Precision …
[PDF][PDF] A Deep Learning-Based Novel Approach for Weed Growth Estimation.
AM Mishra, S Harnal, K Mohiuddin… - … Automation & Soft …, 2022 - researchgate.net
Automation of agricultural food production is growing in popularity in scientific communities
and industry. The main goal of automation is to identify and detect weeds in the crop. Weed …
and industry. The main goal of automation is to identify and detect weeds in the crop. Weed …
Novel cropdocnet model for automated potato late blight disease detection from unmanned aerial vehicle-based hyperspectral imagery
The accurate and automated diagnosis of potato late blight disease, one of the most
destructive potato diseases, is critical for precision agricultural control and management …
destructive potato diseases, is critical for precision agricultural control and management …