RNN model-based classification of wireless capsule endoscopy bleeding images

WCE (wireless capsule endoscopy) is a technique that may be used to diagnose gastrointestinal issues and provide painless gut imaging. Regardless, variety of variables, such as effectiveness, tolerance, safety, performance, make widespread use modification challenging. Furthermore, automated analysis the data essential for detecting anomalies. When patient's digestive system imaged using WCE, vast amount generated these challenges have been addressed computer assisted vision-based technologies, but they do not achieve level precision, further work required. With this work, goal create can automatically analyze images identify problems assist practitioners in making right diagnoses. Finally, comparison SODM-S1 with SODM shows by modifying features increase spatial dependency, our suggested really improve model performance.