Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism

632 indexed citations

Abstract

loading...

About

This paper, published in 2018, received 632 indexed citations. Written by Yong Li, Jiabei Zeng, Shiguang Shan and Xilin Chen covering the research area of Experimental and Cognitive Psychology and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (488 citations), Experimental and Cognitive Psychology (453 citations) and Artificial Intelligence (71 citations). Published in IEEE Transactions on Image Processing.

Countries where authors are citing Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism

Specialization
Citations

This map shows the geographic impact of Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism. 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 Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism more than expected).

Fields of papers citing Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism.

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/10.1109/tip.2018.2886767.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026