Image Segmentation using Optimization Algorithm: A Survey
Image segmentation has proven to be an important step in the processing of images, computer vision algorithms, etc. It splits an image into different regions. This survey reviews major contributions in the healthcare l field using deep learning, including the common problems published over the last few years, and also explains the basics of deep learning concepts applicable to medical image segmentation. To solve current problems and improve the development of medical image segmentation problems, the Efficient Net Atrous convolutional encoder & and decoder can be used for segmentation in future research. Efficient Nets have much better accuracy & and efficiency than conv-Nets. The advantage of Efficient-Net is that it can balance the model's depth, width, and image resolution through composite coefficients.
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