Object Detection and IOU Based on Sensors: Methods and Applications

Dear Colleagues,

With the development of sensors, Intersection over Union (IoU) for object detection based on sensors has been widely used in various fields. Intersection over union is an evaluation metric used to measure the accuracy of an object detector on a particular dataset. Intersection over union can be used to evaluate the performance of HOG + linear SVM object detectors and convolutional neural network detectors (R-CNN, Faster R-CNN, YOLO, etc.).

This Special issue focuses on “Object Detection and IOU Based on Sensors: Methods and Applications”. The Special Issue aims to provide a state-of-the-art overview of object detection, object tracking, and object recognition. Potential topics include, but are not limited to, the following:

• Intersection over union (IoU) for object detection and recognition;
• Convolutional neural networks (CNN) for object detection and recognition;
• YOLO (real-time object detection);
• Sensor and sensing technologies for object detection and recognition;
• Image classification;
• Image segmentation;
• Three-dimensional computer vision;
• Three-dimensional object detection and recognition;
• Visual surveillance and monitoring.

Prof. Dr. Bin Cao
Guest Editor

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