AIMC Topic: Plant Diseases

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Banana Leaves Imagery Dataset.

Scientific data Mar 21, 2025
In this work, we present a dataset of banana leaf imagery, both with and without diseases. The dataset consists of 11,767 images, categorized as follows: 3,339 healthy images, 3,496 images of leaves affected by Black Sigatoka and 4,932 images of leav...
Machine Learning Musa Plant Diseases Plant Leaves Tanzania Fusarium
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Efficient deep learning-based tomato leaf disease detection through global and local feature fusion.

BMC plant biology Mar 11, 2025
In the context of intelligent agriculture, tomato cultivation involves complex environments, where leaf occlusion and small disease areas significantly impede the performance of tomato leaf disease detection models. To address these challenges, this ...
Solanum lycopersicum Plant Diseases Deep Learning Plant Leaves
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On construction of data preprocessing for real-life SoyLeaf dataset & disease identification using Deep Learning Models.

Computational biology and chemistry Mar 8, 2025
The vast volumes of data are needed to train Deep Learning Models from scratch to identify illnesses in soybean leaves. However, there is still a lack of sufficient high-quality samples. To overcome this problem, we have developed the real-life SoyLe...
Glycine max Deep Learning Plant Leaves Plant Diseases
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Leveraging ML to predict climate change impact on rice crop disease in Eastern India.

Environmental monitoring and assessment Mar 8, 2025
Rice crop disease is critical in precision agriculture due to various influencing components and unstable environments. The current study uses machine learning (ML) models to predict rice crop disease in Eastern India based on biophysical factors for...
Oryza Climate Change Agriculture Environmental Monitoring Crops, Agricultural Plant Diseases Machine Learning India
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Leveraging YOLO deep learning models to enhance plant disease identification.

Scientific reports Mar 7, 2025
Early automation in identifying plant diseases is crucial for the precise protection of crops. Plant diseases pose substantial risks to agriculture-dependent nations, often leading to notable crop losses and financial challenges, particularly in deve...
Deep Learning Plant Leaves Fragaria Crops, Agricultural Plant Diseases
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Hybrid feature optimized CNN for rice crop disease prediction.

Scientific reports Mar 6, 2025
The agricultural industry significantly relies on autonomous systems for detecting and analyzing rice diseases to minimize financial and resource losses, reduce yield reductions, improve processing efficiency, and ensure healthy crop production. Adva...
Algorithms Deep Learning Plant Diseases Image Processing, Computer-Assisted Plant Leaves Oryza Neural Networks, Computer Crops, Agricultural
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Sugarcane leaf disease classification using deep neural network approach.

BMC plant biology Mar 4, 2025
OBJECTIVE: The objective is to develop a reliable deep learning (DL) based model that can accurately diagnose diseases. It seeks to address the challenges posed by the traditional approach of manually diagnosing diseases to enhance the control of dis...
Neural Networks, Computer Saccharum Plant Diseases Deep Learning Plant Leaves
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A hybrid deep learning model approach for automated detection and classification of cassava leaf diseases.

Scientific reports Feb 27, 2025
Detecting cassava leaf disease is challenging because it is hard to identify diseases accurately through visual inspection. Even trained agricultural experts may struggle to diagnose the disease correctly which leads to potential misjudgements. Tradi...
Plant Leaves Deep Learning Plant Diseases Algorithms Manihot Image Processing, Computer-Assisted
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Application of deep learning for fruit defect recognition in Psidium guajava L.

Scientific reports Feb 20, 2025
Psidium guajava L. is an important tropical and subtropical fruit. Due to its geographical location and suitable climate, Taiwan produces Psidium guajava L. all year round. Quality standardization is therefore a crucial issue. The primary objective w...
Psidium Fruit Deep Learning Image Processing, Computer-Assisted Plant Diseases Taiwan
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Identification of potent phytochemicals against Magnaporthe oryzae through machine learning aided-virtual screening and molecular dynamics simulation approach.

Computers in biology and medicine Feb 17, 2025
Magnaporthe oryzae stands as a notorious fungal pathogen responsible for causing devastating blast disease in cereals, leading to substantial reductions in grain production. Despite the usage of chemical fungicides to combat the pathogen, their effec...
Fungal Proteins Ascomycota Magnaporthe Molecular Dynamics Simulation Plant Diseases Molecular Docking Simulation Fungicides, Industrial Phytochemicals Machine Learning
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