Recent Advances in Mathematical Research and Computer Science Vol. 3

Abstract

Most industries around the globe make use of image processing to improve their productions. On the other hand Big Data Processing is a big dataset; this required fast method to processing irrespective of Generic nature, therefore Clarification of heterogeneous images can improve the integrity of any system design. To avoid waste of time and energy, it is necessary to classify images. In a clear perspective, the objective of image classification is complex characteristic modalities to categories and label group of pixies or vector within an image based on specific rules. Big Data Processing for Generic Clarification of heterogeneous images provides fast, accurate and objectives results. In this study, the researchers classified into three category using resnet50 techniques for training dataset images. The outcome of the research is analyzing these techniques and comparison analysis on different existing image data sets as pre-trained data and test data as sample images for decision making based on their limitations and strengths.