Image Texture Feature Extraction Using GLCM Approach
- Authors
- P. MohanaiahP. Sathyanarayana
In The Last Decade
doi.org/w37614667 →Countries where authors are citing Image Texture Feature Extraction Using GLCM Approach
This map shows the geographic impact of Image Texture Feature Extraction Using GLCM Approach. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Image Texture Feature Extraction Using GLCM Approach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Image Texture Feature Extraction Using GLCM Approach more than expected).
Fields of papers citing Image Texture Feature Extraction Using GLCM Approach
This network shows the impact of Image Texture Feature Extraction Using GLCM Approach. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Image Texture Feature Extraction Using GLCM Approach.
About Image Texture Feature Extraction Using GLCM Approach
This paper, published in 2013, received 480 indexed citations . Written by P. Mohanaiah and P. Sathyanarayana covering the research area of Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (163 citations), Artificial Intelligence (133 citations) and Radiology, Nuclear Medicine and Imaging (79 citations).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/w37614667.