The Use of Deep Learning in Image Segmentation and Classification

This paper proposed image classification and segmentation techniques using deep learning. Image classification is an advanced method that will be affected by several factors. This paper examines current practices, problems, and prospects of image classification. The emphasis is placed on the summarization of major advanced classification approaches and therefore the techniques used for improving classification accuracy. Additionally, some necessary problems affecting classification performance are mentioned. This literature review suggests that planning a suitable image processing procedure could be a requirement for the successful classification of remotely sensed information into a thematic map. Effective use of multiple options of remotely sensed data and therefore the selection of an appropriate. Image segmentation refers to the partition of an image into completely different regions that are homogeneous or similar and heterogeneous in some characteristics. During a preprocessing stage, an image is over segmented into super pixels by the normalized cut algorithm. Using the various algorithms the present methodologies of image segmentation are reviewed so that user interaction is possible for images. Strategies of image analysis belong to a general knowledge base area of the multidimensional signal process