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[HTML][HTML] Feature engineering to identify plant diseases using image processing and artificial intelligence: A comprehensive review
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 …
plants by human observers for disease identification are time-consuming, costly, and prone …
Tomato leaf diseases classification using image processing and weighted ensemble learning
In ensemble methods, multiple base classifiers with different performances are used to
increase classification accuracy. This study proposes a novel weighted majority voting …
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 …
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 …
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
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 …
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
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 …
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
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 …
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)
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 …
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
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 …
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
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 …
for those affected. PSLs can cause skin cancers, particularly melanoma, which can be life …
Segmentation and classification of dermoscopic skin cancer on green channel
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 …
Hands-on identification of melanoma in its early stages with the unaided eye is error-prone …