Glaucoma prediction using Deep neural networks
Glaucoma prediction using Deep neural networks
Successfully developed Convolutional Neural Network (CNN) model that achieved an accuracy rate of 93%. This model has the capability to predict both the presence of Glaucoma and its corresponding stage. The effectiveness of this research was showcased through a presentation at the esteemed ICACECS 2020 conference. The implementation of this advanced CNN model was accomplished using Python and cutting-edge Deep Learning techniques, further underscoring its significance in the field of medical image analysis.
Successfully developed Convolutional Neural Network (CNN) model that achieved an accuracy rate of 93%. This model has the capability to predict both the presence of Glaucoma and its corresponding stage. The effectiveness of this research was showcased through a presentation at the esteemed ICACECS 2020 conference. The implementation of this advanced CNN model was accomplished using Python and cutting-edge Deep Learning techniques, further underscoring its significance in the field of medical image analysis.
Tech stack:: Python, Supervised ML
Tech stack:: Python, Supervised ML
Image character recognition
Image character recognition
Image character recognition is used for extracting the characters from any kind of image. It can be used for searching/copying/editing in handwritten documents.
Image character recognition is used for extracting the characters from any kind of image. It can be used for searching/copying/editing in handwritten documents.
Tech stack: Java, nosql database, character recognition API
Tech stack: Java, nosql database, character recognition API
Take-ATrip
Take-ATrip
Developed a Responsive website to book hotels, and travel packages. This is hosted on heroku.
Developed a Responsive website to book hotels, and travel packages. This is hosted on heroku.
Tech stack:: MEAN stack, Heroic
Tech stack:: MEAN stack, Heroic