ECS795P Deep Learning and Computer Vision, 2025/26
Online Assessment for Coursework 1: Introduction to Transformer
Aim: To obtain practical knowledge and hands-on understanding of the concepts of self-attention, transformers and the application on image classification.
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Each student is assigned with one Q(Question) and one E(Exercise) randomly sampled from the CW1 guideline.
Answering other questions from the guideline will result in 0 marks regardless of the correctness.
The duration of this online assessment is 120 minutes.
Submission due is 13:00 28th March, with no exception and no late submission allowed.
Submission format: a single PDF file including answers for both question and exercise. Copy-paste your code for the exercise into the pdf file submission rather than standlone individual python files.
You must refer to the coursework's guideline for the full description of questions/exercises as well as the context.
The index "Qi.j" means the j-th question of the "The questions to think over" in the i-th part of the guideline. The same applies to the exercise - "Ei.j".
Contact any demonstrator without delay if you encounter any unexpected issues，e.g. you failed to get your
Q/E using your student ID or you suddenly failed to access the webpage.
Demonstrators won't give hints nor check the answer during the online assessment.
Demonstrators won't debug the code, including any issue regarding the programming environment during
the assessment.
Student Information
Question to be answered (Q1.1)
Exercise to be conducted (E1.5)
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