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Full-Text Articles in Engineering
Benchmarking Of Embedded Object Detection In Optical And Radar Scenes, Vijaysrinivas Rajagopal
Benchmarking Of Embedded Object Detection In Optical And Radar Scenes, Vijaysrinivas Rajagopal
Masters Theses
A portable, real-time vital sign estimation protoype is developed using neural network- based localization, multi-object tracking, and embedded processing optimizations. The system estimates heart and respiration rates of multiple subjects using directional of arrival techniques on RADAR data. This system is useful in many civilian and military applications including search and rescue.
The primary contribution from this work is the implementation and benchmarking of neural networks for real time detection and localization on various systems including the testing of eight neural networks on a discrete GPU and Jetson Xavier devices. Mean average precision (mAP) and inference speed benchmarks were performed. …
Learning With Limited Labeled Data For Image And Video Understanding, Razieh Kaviani Baghbaderani
Learning With Limited Labeled Data For Image And Video Understanding, Razieh Kaviani Baghbaderani
Doctoral Dissertations
Deep learning-based algorithms have remarkably improved the performance in many computer vision tasks. However, deep networks often demand a large-scale and carefully annotated dataset and sufficient sample coverage of every training category. However, it is not practical in many real-world applications where only a few examples may be available, or the data annotation is costly and require expert knowledge. To mitigate this issue, learning with limited data has gained considerable attention and is investigated thorough different learning methods, including few-shot learning, weakly/semi supervised learning, open-set learning, etc.
In this work, the classification problem is investigated under an open-world assumption to …