PBL Student Case Snapshot – SEC, Nepal

 IMAGE COLORIZATION USING CONVOLUTIONAL NEURAL NETWORK

With its advent and extension in many areas, technology has become crucially integrated with human lifestyle and activities. Various branches of technology have found ways to progress, and they serve imperatively in various fields of development, entertainment and utility. Artificial Intelligence and domains within it encompass a huge portion of technological applications, and deep learning being a subset of AI can be used for many such implementations. Image restoration is one such domain which can utilize the deep learning capabilities of a machine to effectively produce results. Colorization of gray-scale images is generally carried out using photo editing software and is a tedious and expensive job. Hence, our project makes this process automated and accurate utilizing the convolutional neural architecture combined with EfficientNetB0. In this project, we have realized and implemented several compositions of the baseline CNN model with pre-trained models to deduce the best version. The system is integrated into a mobile application making use of Flutter for cross-platform development. 

Mentor

Bharat Bhatta, Senior Lecturer, Department of Electronics and Computer Engineering.

Associated courses:

Project (Part A) CT785

Project (Part B) CT755

Time Frame: 

Course: 01/2020 - 08/2020

Field visits: 08/06/2021 & 12/04/2022

Final Outcomes:

Image Gallery

Report

Presentation Slides