DEVELOPMENT OF LIGHT WEIGHT DEEP LEARNING IOT INTERFACE ALGORITHM FOR BIOMEDICAL IMAGE ANALYSIS
Biomedical engineering and healthcare sectors are one of the most crucial areas of an industry. The image analysis always been a first level decision maker for experts. Image analysis now-a-days not remained limited for medical and biomedical applications but also extended for many other applications like plant pathological use to identify pant/crop diseases or algae studies. Also, the concept of Internet of Things is now not limited to connect core things but eventually can be used as an interface for deep learning modules to club the benefits of both technologies. Hence, this paper presents the development of light weight deep learning IoT interface where it is proved that, IoT interface can boost the capability of identification of image parameters to the actual user interface. The accuracy can be boosted as compared to existing deep learning modules and also segmentation images can be uploaded to Hadoop Big data server.
IoT; deep learning; machine learning; image analysis