Object detection is one of the important problems for autonomous robots. Faster R-CNN, one of the state-of-the-art object detection methods, approaches real time application; nevertheless, ...

Object Detection Comparision between YOLOv3 and Faster RCNN This project compares two object detection models YOLOv3 and Faster R-CNN on the PSU Car Dataset containing aerial images. The goal is to ...

Going in the case of object detection where CNN is very helpful, we have three region-based CNN models which we call R-CNN, ... Comparison: R-CNN: Fast R-CNN: Faster R-CNN: region proposals method: ...

It aims to enable object detection on microcontrollers in the power domain of milliwatts, with less than 0.5MB memory available for storing convolutional neural network (CNN) weights. The proposed ...

For instance Bergmann et al. (2019) proposed Tracktor++ to use a CNN to perform both object detection and tracking. Similarly, ... large patch sizes such as 256 × 256 and 512 × 512 obtained large ...

Object detection is one of the important problems for autonomous robots. Faster R-CNN, one of the state-of-the-art object detection methods, approaches real time application; nevertheless, ...

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