2. An overview of skin lesion segmentation, features engineering, and classification

Sabri, My Abdelouahed; Filali, Youssef; Ennouni, Assia; Yahyaouy, Ali; Aarab, Abdellah

doi:10.1515/9783110621105-002

Cited by 5 publications

(1 citation statement)

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“…Early detection could be fruitful and beneficial. So, the application of computer vision and machine learning algorithms are recently used to help and assist decision makers in medicine or supervision [19,20].…”

Section: Introductionmentioning

confidence: 99%

Plant Diseases Detection and Classification Based on Image Processing

2020

IJEAT

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To further the progress of sustainable development and solve real-life problems we have seen many processes are applied in our life, like artificial intelligence and decisionmaking. Morocco is one of the countries that rely heavily on agriculture and food production. So, food production is considered the basic needs of a human being for that we have seen fast advancements in agriculture productivity to meet the projected demand. However, with the time passing by, all species of plants are subjected to various types of diseases that cause huge damage. Although the observation of variation in the infected part of the leaf plant is very important but not enough because the perception of the human eye is not so much stronger. The identification of plant diseases is a very important task in the agriculture area. So, the best identification means there is a huge gain on agricultural productivity, quality, and quantity. To detect plant diseases in an earlier stage we require efficient and precise techniques to assist farmers in decision-making. This article presents, first, an overview of plant diseases from leaves images and different disease classification approaches that can be used for plant leaf disease detection.

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Section: Introductionmentioning

confidence: 99%