Object Detection1

object detection

Object detection is the process of detecting objects of interests in images or video frames using pre-trained networks. It is one of the main functionalities of a vision-based AI system. Recently, several innovations in the field of object detection has been introduced that provides robust and high performance solutions for the problem. Object detection is between the most interesting services of saiwa©. With the following simple interactive interface, one may try the two state-of-the-art networks, i.e. Detectron2 and YOLOv5, easily. For more technical discussion on the two networks, please refer to the object detection white paper. By default the two networks are trained over COCO dataset which consists 12 classes and 80 objects (For a list of default objects see “Advanced Settings” below). Upon your interest, we at saiwa© re-train the networks on your specific dataset. Then using the same interface you can find any other objects from your application. You only need to fill up the request form using “Request for customization” option. Additionally, you can re-train the both networks yourself using saiwa© “Deep Learning” service. The features of saiwa© object detection service:

 

  • Providing state-of-the-art algorithms
  • Detecting, localizing and segmenting regions of interests (ROIs)
  • Complete user control over the amount of uncertainty of detected objects (by setting “Confidence” parameter in “Advanced Settings”)
  • Exporting and archiving the results in user cloud space or locally
  • Modifying the objects
  • Re-train the same networks over user-defined datasets using “Deep Learning” service
  • Request for re-train the networks over user-defined datasets by saiwa© team using “Request for customization” option
  • Apply on several images
  • Preview and download the resulting images or detailed information of detected objectsObject detection applications include but are not limited to:
    1- Industrial applications like:
    a. Detecting objects of interests over conveyers
    b. Tracking workers and vehicles
    c. Product classification
    2- Surveillance and security
    3- Urban applications like:
    a. Detecting cars, pedestrians, bicycles and etc.
    b. Traffic monitoring
    4- Robot or self-driving vision
    5- Medical applications like:
    a. Detecting tumor in CT images
    b. Diabetic retinopathy diagnosis

 

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