Tanzila Saba
Papers
6
Total Citations
478
H-Index
5
About
Dr. Tanzila Saba is a leading researcher in artificial intelligence and computer vision, whose work centers on deep learning, feature fusion, and intelligent human action recognition. She has made seminal contributions to developing sustainable deep learning frameworks that enhance object recognition accuracy for autonomous systems and visual surveillance. Her highly cited 2019 paper on hand-crafted and deep convolutional neural network features fusion for human action recognition has garnered 154 citations, while her 2020 work on multi-layers deep features fusion for object recognition has received 153 citations, demonstrating her profound impact on the field. Dr. Saba has also advanced gender recognition from pedestrian appearance using stacked autoencoders (99 citations) and pioneered explainable AI for sign language recognition through ensemble learning (57 citations). Her research addresses critical challenges in robotics, human-computer interaction, and intelligent surveillance, making her a pivotal figure in applied deep learning. Despite a retracted paper, her core contributions continue to shape modern AI-driven recognition systems.
Research Focus
Key Achievements
Top Papers
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- 6Image Fusion Using Wavelet Transformation and XGboost Algorithm5 citations · 2024