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What is Co-Occurrence Matrix

Handbook of Research on AI Methods and Applications in Computer Engineering
It is a matrix that represents the distance and angular spatial relationship over an image sub region it is used as a texture analysis approach.
Published in Chapter:
Smart Farming: Automatic Detection and Classification of Olive Leaf Diseases
Imen Fourati Kallel (Ecole Nationale d'Electronique et des Télécommunications de Sfax (ENET'Com), Tunisia), Mohamed Kallel (Ecole Nationale d'Electronique et des Télécommunications de Sfax (ENET'Com), Tunisia), Mahmoud Ghorbel (Centre de Recherche en Numérique de Sfax (CRNS), Tunisia), and Mohamed Ali Triki (The Olive Tree Institute of Tunisia, Tunisia)
DOI: 10.4018/978-1-6684-6937-8.ch015
Abstract
Olive trees diseases harm the quality and the quantity of the harvest seriously, which causes considerable economic losses for farmers, and more importantly affects the national economy in its entirety. The aim of this investigation is to work out a recognizing pattern method, based on the analysis of the texture and supervised classification. It essentially detects and classifies olive tree diseases in order to provide the farmers with tools helping them not only to get informed of their trees' diseases, but also to know how to treat them effectively.
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Information Retrieval Systems in Healthcare: Understanding Medical Data Through Text Analysis
A co-occurrence matrix is a square matrix that represents the frequency of how often pairs of items, such as words, occur together in a given dataset or context. In natural language processing, it is used to analyze relationships between words in a text corpus. Each element in the matrix reflects the number of times two items appear together within a specified window of proximity, aiding in capturing semantic relationships and contextual information.
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Exploring New Handwriting Parameters for Writer Identification
A statistical matrix use for measuring texture in images. Could be considered an image by itself.
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