Projects Handled

1. Skin Disease Detection System by CNN

The main objective of this project was to detect and categorize skin cancer especially benign or malignant by the use of CNN. Based mainly on the test sets used to train, it collects necessary parameters from the given test sets. The parameters are then processed by the different layers. Those layers are important to convert the collected parameters to meaningful result. The result is then analyzed to give output to the user. This system tries to predict best possible result, ease the process of skin disease diagnosis, makes the process faster as well as produce more accurate result. Mastering the use of CNN and this system will surely revolutionize the traditional process of skin disease diagnosis and will make diagnosis process simple, cheaper and easily available.

2. Grayscale Image/Video Colorization Using Generative Adversarial Network

The main objective of this project was to use GAN for image colorization and further implementation in videos. Based mainly on the images used to train, it collects necessary color information from the given data sets. The information is then processed by the different layers. Those layers are important to convert the collected color information to meaningful weights. These weights are used to colorize the image/video and output is passed to user. This system tries to predict best possible color, ease the process of image and video colorization, makes the process faster as well as produces more accurate result. Mastering the use of GAN and this system will surely revolutionize the traditional process of image/video colorization and will make process simple and easily available.