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Found 9 papers, 1 papers with code
Heart Rate Detection Using an Event Camera
Ground-truth HR measurements obtained using conventional methods were used to evaluate of the accuracy of automatic detection of HR from event camera data.
Neuromorphic Seatbelt State Detection for In-Cabin Monitoring with Event Cameras
In a binary classification task, the fastened/unfastened frames were identified with an F1 score of 0. 989 and 0. 944 on the simulated and real test sets respectively.
Decisive Data using Multi-Modality Optical Sensors for Advanced Vehicular Systems
Optical sensors have played a pivotal role in acquiring real world data for critical applications.
Development, Optimization, and Deployment of Thermal Forward Vision Systems for Advance Vehicular Applications on Edge Devices
In this research work, we have proposed a thermal tiny-YOLO multi-class object detection (TTYMOD) system as a smart forward sensing system that should remain effective in all weather and harsh environmental conditions using an end-to-end YOLO deep learning framework.
Event-based YOLO Object Detection: Proof of Concept for Forward Perception System
The focus is on building efficient state-of-the-art object detection networks with better inference results for fast-moving forward perception using an event camera.
Control and Evaluation of Event Cameras Output Sharpness via Bias
To increase the users degree of freedom in controlling the output of these cameras, such as changing the sensitivity of the sensor to light changes, controlling the number of generated events and other similar operations, the camera manufacturers usually introduce some tools to make sensor level changes in camera settings.
Recurrent Super-Resolution Method for Enhancing Low Quality Thermal Facial Data
The process of obtaining high-resolution images from single or multiple low-resolution images of the same scene is of great interest for real-world image and signal processing applications.
Evaluation of Thermal Imaging on Embedded GPU Platforms for Application in Vehicular Assistance Systems
This study is focused on evaluating the real-time performance of thermal object detection for smart and safe vehicular systems by deploying the trained networks on GPU & single-board EDGE-GPU computing platforms for onboard automotive sensor suite testing.
Object Detection in Thermal Spectrum for Advanced Driver-Assistance Systems (ADAS)
Object detection in thermal infrared spectrum provides more reliable data source in low-lighting conditions and different weather conditions, as it is useful both in-cabin and outside for pedestrian, animal, and vehicular detection as well as for detecting street-signs & lighting poles.
