AIMC Topic: Plant Leaves

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A novel hybrid fruit fly and simulated annealing optimized faster R-CNN for detection and classification of tomato plant leaf diseases.

Scientific reports
Modern agriculture increasingly relies on technologies that enhance farmers' efficiency and economic growth. One challenge is the accurate identification of disease-affected plants, whose characteristics like structure, size, texture, and color can v...

Estimation of mesophyll conductance in Ginkgo biloba from the PSII redox state using a machine learning approach.

Tree physiology
Mesophyll conductance (gm) has been proved to be one of the important factors limiting photosynthesis and thus affects the estimation of plant productivity and terrestrial carbon balance. However, beyond the leaf scale, gm is usually assumed to be in...

Lightweight wavelet-CNN tea leaf disease detection.

PloS one
Tea diseases can significantly impact crop yield and quality, necessitating accurate and efficient recognition methods. This study presents WaveLiteNet, a lightweight model designed for tea disease recognition, addressing the challenge of inadequate ...

Segmentation-based lightweight multi-class classification model for crop disease detection, classification, and severity assessment using DCNN.

PloS one
Leaf diseases in Zea mays crops have a significant impact on both the calibre and volume of maize yield, eventually impacting the market. Prior detection of the intensity of an infection would enable the efficient allocation of treatment resources an...

Early and late blight disease identification in tomato plants using a neural network-based model to augmenting agricultural productivity.

Science progress
Computer-advanced technologies have a significant impact across various fields. It is widely recognized that diseases have a detrimental effect on crop productivity and can significantly impact the economy, particularly in agricultural countries. Tom...

Machine learning for image-based multi-omics analysis of leaf veins.

Journal of experimental botany
Veins are a critical component of the plant growth and development system, playing an integral role in supporting and protecting leaves, as well as transporting water, nutrients, and photosynthetic products. A comprehensive understanding of the form ...

Integrating a crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning.

Journal of experimental botany
A major challenge for the estimation of crop traits (biophysical variables) from canopy reflectance is the creation of a high-quality training dataset. To address this problem, this research investigated a conceptual framework by integrating a crop g...

Different stages of disease detection in squash plant based on machine learning.

Journal of biosciences
To increase agriculture production, accurate and fast detection of plant disease is required. Expert advice is needed to detect disease in plants, nutrition deficiencies or any other abnormalities caused by extreme weather conditions. But this proces...

Machine Learning for Image Analysis: Leaf Disease Segmentation.

Methods in molecular biology (Clifton, N.J.)
Plant phenomics field has seen a great increase in scalability in the last decade mainly due to technological advances in remote sensors and phenotyping platforms. These are capable of screening thousands of plants many times throughout the day, gene...

Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms.

Plant physiology
Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield, thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models use multi-source data from unmanned aerial vehicles (UAVs), but ...