Assignment tasks This assignment will focus on Image Segmentation using the ADE20K dataset. This is an individual assignment where each student will produce a report on the data analysis they will perform. You are encouraged to utilise Google Colab for the coding part of your assignment. https://herts.instructure.com/courses/129101/assignments/406384 1/86/17/26, 12:10 PM Assignment 2 - Individual project - Image segmentation - 25% You will explain and discuss the data processing, the method(s) you make use of and elaborate the outcome. You will work on the ADE20K dataset (explained below in more detail) to research viable models to train, discuss different approaches to explore and visualise the data (i.e., perform EDA), build a tool to pre-process the dataset, and customise your chosen model(s) to improve performance. You will produce a code that does semantic segmentation of the 4 classes targeted in this assignment: person, car, book, airplane. In more detail, your model(s) should identify which of these 4 classes the region of the image corresponds to, and should be applicable to any unlabelled image. To be clear: doing only binary segmentation (i.e. any class vs background) will result in a very large penalty, as you will be considered not to have done the required task. You may use more than one model, but one has to be trained partially or fully by you. Should you use more than one, you are encouraged to compare your main trained model with one or more pre-trained models.
Megaminds has supported academic requirements in this discipline and related disciplines.