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Deep learning implementation of image segmentation in agricultural applications: A comprehensive review
L Lei, Q Yang, L Yang, T Shen, R Wang… - Artificial Intelligence …, 2024 - Springer
Image segmentation is a crucial task in computer vision, which divides a digital image into
multiple segments and objects. In agriculture, image segmentation is extensively used for …
multiple segments and objects. In agriculture, image segmentation is extensively used for …
Recent advances in plant disease severity assessment using convolutional neural networks
T Shi, Y Liu, X Zheng, K Hu, H Huang, H Liu… - Scientific Reports, 2023 - nature.com
In modern agricultural production, the severity of diseases is an important factor that directly
affects the yield and quality of plants. In order to effectively monitor and control the entire …
affects the yield and quality of plants. In order to effectively monitor and control the entire …
[HTML][HTML] Comparing YOLOv8 and Mask R-CNN for instance segmentation in complex orchard environments
Instance segmentation, an important image processing operation for automation in
agriculture, is used to precisely delineate individual objects of interest within images, which …
agriculture, is used to precisely delineate individual objects of interest within images, which …
Automatic recognition of rice leaf diseases using transfer learning
Rice, the world's most extensively cultivated cereal crop, serves as a staple food and energy
source for over half of the global population. A variety of abiotic and biotic factors such as …
source for over half of the global population. A variety of abiotic and biotic factors such as …
[HTML][HTML] Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques
Rice is an essential food crop that is cultivated in many countries. Rice leaf diseases can
cause significant damage to crop cultivation, leading to reduced yields and economic …
cause significant damage to crop cultivation, leading to reduced yields and economic …
Segmentation of dry bean (Phaseolus vulgaris L.) leaf disease images with U-Net and classification using deep learning algorithms
Detecting plant diseases is a challenging and time-consuming task that requires expertise
and laboratory conditions. Deep learning methods have been proposed as a solution to this …
and laboratory conditions. Deep learning methods have been proposed as a solution to this …
A disease monitoring system using multi-class capsule network for agricultural enhancement in muskmelon
For any agricultural society, the well-being of the plants is crucial to achieve a greater yield.
The health and vigor of plants play a pivotal role in sha** the ultimate outcome of crop …
The health and vigor of plants play a pivotal role in sha** the ultimate outcome of crop …
[PDF][PDF] Early-Stage Brown Spot Disease Recognition in Paddy Using Image Processing and Deep Learning Techniques.
Accepted: 5 December 2021 India is an agricultural country. Paddy is the main crop here on
which the livelihood of millions of people depends. Brown spot disease caused by fungus is …
which the livelihood of millions of people depends. Brown spot disease caused by fungus is …
An artificial-intelligence-based novel rice grade model for severity estimation of rice diseases
The pathogens such as fungi and bacteria can lead to rice diseases that can drastically
impair crop production. Because the illness is difficult to control on a broad scale, crop field …
impair crop production. Because the illness is difficult to control on a broad scale, crop field …
AISOA-SSformer: An Effective Image Segmentation Method for Rice Leaf Disease Based on the Transformer Architecture
Rice leaf diseases have an important impact on modern farming, threatening crop health
and yield. Accurate semantic segmentation techniques are crucial for segmenting diseased …
and yield. Accurate semantic segmentation techniques are crucial for segmenting diseased …