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Gain access to 6 different categories of resources, from open-source fact-checking tools to MOOCs and digital safety material, to come up with solutions that can help further improve MIL and tackle infodisorder.
- Acceleration Hub
During this program, to accelerate the generation of...
- DIP: Digital Innovations for Peace
To achieve this, LI will bring together creative...
- Acceleration Hub
During this program, to accelerate the generation of innovative media solutions, we invited digital media startups, entrepreneurs and media professionals to join our DIP project acceleration hub.
Learn all about the process of converting an image/video into digital form by performing tasks like noise reduction, filtering, auto exposure, autofocus, HDR correction, and image sharpening with a Specialized type of media processor. Image Processing techniques using OpenCV and Python.
In this blog, you will find the 600 latest digital image processing projects for beginners and engineering students. These DIP projects are useful for BTech and MTech students. Scene Understanding and Labeling with Deep Learning for Smart Cities.
Support materials are packaged in the DIP4E Support Packages for faculty and students. These materials consist of homework problem solutions, project solutions, MATLAB functions, and image databases. Please click on the appropriate link below to apply for a DIP4E Support Package.
Contribute to Eskay81/DIP development by creating an account on GitHub. We read every piece of feedback, and take your input very seriously.
To achieve this, LI will bring together creative entrepreneurs, digital technology activists and media professionals to support the development of innovative media and information literacy solutions, with a special focus on tackling disinformation.
