T. Thenmozhi
Papers
2
Total Citations
30
H-Index
2
About
T. Thenmozhi is a researcher focused on computer vision, video surveillance, and biomedical signal processing. Her work primarily addresses motion detection in surveillance systems and the classification of motor imagery EEG signals using machine learning techniques. In her most-cited paper, "Adaptive motion estimation and sequential outline separation based moving object detection in video surveillance system" (2020), she proposed a novel method for detecting moving objects in video streams, which has garnered 28 citations. However, this paper has since been retracted, a notable development that underscores the importance of research integrity. Her subsequent work, "An Improved Approach for Extracting Features and Classifying Motor Imagery EEG Signals Through Machine Learning" (2021), explores brain-computer interface applications, though it has received only 2 citations to date. Despite the retraction, Thenmozhi's contributions to adaptive motion estimation and EEG signal classification reflect her engagement with real-time video analysis and neural signal processing, areas with significant potential for intelligent systems and assistive technologies.
Research Focus
Key Achievements
Top Papers
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- 2