Segmentation of Deep Learning Models

In applications such as disease detection, crop management, weed management, robotics, augmented reality, and medical image analysis, image segmentation is widely used. Image segmentation is a method of dividing a digital photo into several segments (units of pixels, frequently referred to as image objects). Using the image segmentation technique, it is easy for researchers to research and recognize the illustration of an image. In this chapter, various algorithms, including the threshold method, edge-based technique, clustering technique, and watershed method, are explained. Deep learning models about segmentation as a whole have been envisioned in many applications, including overall performance, with the computer images and presenter aiming to develop an image segmentation approach. Based on segmentation, we interpret the similarities, benefits, and drawbacks of these deep-learning models.