Which method is best for object detection?

It forms the basis of many other downstream computer vision tasks, for example, instance segmentation, image captioning, object tracking, and more. Specific object detection applications include pedestrian detection, people counting, face detection, text detection, pose detection, or number-plate recognition.

It forms the basis of many other downstream computer vision tasks, for example, instance segmentation, image captioning, object tracking, and more. Specific object detection applications include pedestrian detection, people counting, face detection, text detection, pose detection, or number-plate recognition.

This model detects objects defined in the COCO dataset, which is a large-scale object detection, segmentation, and captioning dataset . You can find more information here. The model is capable of detecting 80 classes of objects. (SSD stands for Single Shot MultiBox Detection).

This model detects objects defined in the COCO dataset, which is a large-scale object detection, segmentation, and captioning dataset . You can find more information here. The model is capable of detecting 80 classes of objects. (SSD stands for Single Shot MultiBox Detection).

android-yolo is the first implementation of YOLO for TensorFlow on an Android device. It is compatible with Android Studio and usable out of the box .

android-yolo is the first implementation of YOLO for TensorFlow on an Android device. It is compatible with Android Studio and usable out of the box .