Which of the Following is feature of YOLO algorithm*1 pointSingle CNN simultaneously predicts the bounding boxes and class probabilities for these boxes.Extremely fast. (Base network runs at 45fps with no batch processing)You only(Network) looks at the input image and predicts what objects are presentAll the above

In YOLO 2, the training is done on different image sizes starting from ______ to ________*1 point32x32 , 512x51264x64 , 1024x 102432x320 , 608x680320x320 ,608x608

Difference between YOLO,ALEXNET,VGG-16,VGG-19 and MOBILE NET in terms of CNN layer and working Criteria in each layer involved in given pre-trained model.

Mask R-CNN adds a branch to the Faster R-CNN model to also predict:Question 24Answera.Object bounding boxesb.Object categoriesc.Image resolutiond.Semantic Segmentation masks

Describe the existing methodologies for Image Preprocessing on the yolov8 algorithm model for identifying and detecting objects by using the onnx framework

Which of the following results does an object detection model typically return for an image?Question 12Answera.A bounding box with the colour values of the main objectb.Bounding box coordinates that indicate the region of the image where all of the objects it contains are locatedc.A class label, probability, and bounding box for each object in the imaged.A class label and probability score for the image