A state of art review on image analysis techniques, datasets and applications

摘要

The demand for faster algorithms that can extract information from images is becoming increasingly crucial due to the continuously growing volume of image data in practically all disciplines. When using photos in your research, studies, and presentations, it is crucial to assess and evaluate them. Images, like any other source, should be evaluated and reviewed in order to determine their quality, dependability, and appropriateness. Images need to be examined and appraised on several levels. Researchers employ a wide range of methods and datasets for various kinds of image analysis. However, it is still important to survey, analyze, and describe the characteristics and significance of methodologies with support in a variety of applications that will be helpful for new researchers and everyone. The novelty of this review paper is to study the various types of image analysis techniques and datasets used in analyzing the images to detect, identify, and predict disease or any other useful insight content, which are used in various numerous applications such as the medical field, robot vision, pattern recognition, plant disease detection and prediction, and so on.