Object Detection Based on Vision Sensors and Neural Network
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This Special Issue reprint provides an overview of object detection in images and videos, with a focus on addressing the resource constraints of lightweight vision sensors. Object detection has long been a key research area in computer vision. It is now gaining increasing attention from both academia and industry, driven by the rapid advancement of deep neural networks (DNNs) and high-resolution vision sensors. While DNNs have achieved remarkable success in recent years, they are becoming increasingly complex, with deeper network structures and larger training datasets. This growing complexity...
This Special Issue reprint provides an overview of object detection in images and videos, with a focus on addressing the resource constraints of lightweight vision sensors. Object detection has long been a key research area in computer vision. It is now gaining increasing attention from both academia and industry, driven by the rapid advancement of deep neural networks (DNNs) and high-resolution vision sensors. While DNNs have achieved remarkable success in recent years, they are becoming increasingly complex, with deeper network structures and larger training datasets. This growing complexity poses a challenge for deploying computationally and data-intensive DNNs on resource-limited vision sensors, particularly for real-time object detection.
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