Blood Content Prediction using Deep Learning Techniques

Abstract

Cells in the human circulatory system and identifying the types and its functionalities cannot be done through naked eye. This asks for greater accurate methods of visualizing it and hence is vital in understanding blood disease causes, symptoms and the solution for them. But this field lacked clearance for the imaging system. Image Recognition was innovated using Deep Learning Technique.Human body cells assume an astounding job in the human resistant framework. To know more about blood-related infections and its effects, pathologists need to think about the attributes of cells. To diagnose a blood related disease, we need to identify and characterize blood samples of patients. In the medical field, automation for detecting and classifying blood cells and its subtypes have gained more importance nowadays. Recognition of an object is a basic piece for the vision of a computer that distinguishes an article in the given picture regardless of foundations, impediment, lighting or the edge of the view. Problems that are too difficult to solve can be handled using architectures that run deep using algorithms that dive deeper into the features extracted from the input and this can be possible using Deep Learning.