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The image folders are deliberated, and the filter technique is utilized to decrease the images specifically adaptive median filter in our suggested proposal. Gray level co-occurrence matrix (GLCM), grey level run length matrix (GLRLM) and Scale invariant feature transform (SIFT) feature skills are present after filtrating the feature withdrawal. After this, the organization technique is performed, specifically artificial neural network with fuzzy interface system (ANFIS) method; with the help of this organization, exaggerated and non-affected images are categorized. Affected hemorrhage images are transpired for segmentation procedure, and in this exertion, threshold optimization is measured with numerous optimization methods; on the basis of this, particle swarm optimization is accomplished in improved manner. Consequently, the segmented images are projected, and the sensitivity is great when associating with accurateness and specificity in the MATLAB platform.<\/jats:p>","DOI":"10.1515\/jisys-2016-0354","type":"journal-article","created":{"date-parts":[[2018,9,27]],"date-time":"2018-09-27T05:04:08Z","timestamp":1538024648000},"page":"681-697","source":"Crossref","is-referenced-by-count":3,"title":["Effective Approach to Classify and Segment Retinal Hemorrhage Using ANFIS and Particle Swarm Optimization"],"prefix":"10.1515","volume":"27","author":[{"given":"Lawrence Livingston Godlin","family":"Atlas","sequence":"first","affiliation":[{"name":"Computer Science and Information Technology , Maria College of Engineering and Technology , Attor , India"}]},{"given":"Kumar","family":"Parasuraman","sequence":"additional","affiliation":[{"name":"Center for Information Technology and Engineering , Manonmaniam Sundaranar University , Tirunelveli , India"}]}],"member":"374","published-online":{"date-parts":[[2017,5,12]]},"reference":[{"key":"2025120523275899589_j_jisys-2016-0354_ref_001_w2aab3b7c12b1b6b1ab1b5b1Aa","doi-asserted-by":"crossref","unstructured":"M. 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