[HTML][HTML] Feature engineering to identify plant diseases using image processing and artificial intelligence: A comprehensive review

SM Javidan, A Banakar, K Rahnama… - Smart Agricultural …, 2024‏ - Elsevier
Plant diseases can significantly reduce crop yield and product quality. Visual inspections of
plants by human observers for disease identification are time-consuming, costly, and prone …

Tomato leaf diseases classification using image processing and weighted ensemble learning

SM Javidan, A Banakar, KA Vakilian… - Agronomy …, 2024‏ - Wiley Online Library
In ensemble methods, multiple base classifiers with different performances are used to
increase classification accuracy. This study proposes a novel weighted majority voting …

Early detection and spectral signature identification of tomato fungal diseases (Alternaria alternata, Alternaria solani, Botrytis cinerea, and Fusarium oxysporum) by …

SM Javidan, A Banakar, KA Vakilian, Y Ampatzidis… - Heliyon, 2024‏ - cell.com
Early identification of plant fungal diseases is critical for timely treatment, which can prevent
significant agricultural losses. While molecular analysis offers high accuracy, it is often …

Diagnosing the spores of tomato fungal diseases using microscopic image processing and machine learning

SM Javidan, A Banakar, KA Vakilian… - Multimedia Tools and …, 2024‏ - Springer
Accurate diagnosis of plant diseases by the assessment of pathogen presence to reduce
disease-related production loss is one of the most fundamental issues for farmers and …

Melanoma detection using an objective system based on multiple connected neural networks

L Ichim, D Popescu - IEEE Access, 2020‏ - ieeexplore.ieee.org
Melanoma is a common form of skin cancer that dangerously affects many people around
the world. Detection of melanoma with the naked eye by dermatologists may be subject to …

[HTML][HTML] Towards accurate diagnosis of skin lesions using feedforward back propagation neural networks

S Moldovanu, CD Obreja, KC Biswas, L Moraru - Diagnostics, 2021‏ - mdpi.com
In the automatic detection framework, there have been many attempts to develop models for
real-time melanoma detection. To effectively discriminate benign and malign skin lesions …

[HTML][HTML] Accelerating retinal fundus image classification using artificial neural networks (ANNs) and reconfigurable hardware (FPGA)

A Ghani, CH See, V Sudhakaran, J Ahmad… - Electronics, 2019‏ - mdpi.com
Diabetic retinopathy (DR) and glaucoma are common eye diseases that affect a blood
vessel in the retina and are two of the leading causes of vision loss around the world …

Automatic skin lesions detection from images through microscopic hybrid features set and machine learning classifiers

J Alyami, A Rehman, T Sadad… - Microscopy …, 2022‏ - Wiley Online Library
Skin cancer occurrences increase exponentially worldwide due to the lack of awareness of
significant populations and skin specialists. Medical imaging can help with early detection …

Boosting the performance of pretrained CNN architecture on dermoscopic pigmented skin lesion classification

ES Nugroho, I Ardiyanto… - Skin Research and …, 2023‏ - Wiley Online Library
Abstract Background Pigmented skin lesions (PSLs) pose medical and esthetic challenges
for those affected. PSLs can cause skin cancers, particularly melanoma, which can be life …

Segmentation and classification of dermoscopic skin cancer on green channel

H Abouche, A Jimi, N Zrira… - 2022 IEEE/ACM …, 2022‏ - ieeexplore.ieee.org
Melanoma the most dangerous type of skin cancer, has been on the rise in recent years.
Hands-on identification of melanoma in its early stages with the unaided eye is error-prone …