Yi Zhou

• The National Second Prize of RoboMaster Competition, 08.2021
• Academic First Class Scholarship, 01.2022
• Shanghai Scholarship, 12.2022
• Outstanding Graduates of Shanghai, 07.2023

Machine Learning programming

• In the first part, we propose to learn inverse dynamics via linear regression. Train a linear regression model with linear basis functions and implement K-Means algorithm to find suitable cluster centers. Only use numpy and matplotlib.
• In the second part, we use the library PyTorch to define and train a CNN to Implement sharpening, edge detection and Gaussian blur functions. Briefly, learn on how to use pre-training networks to reduce training time

Computer Vision programming

• implement Gaussian filtering, Fourier transform, Edge detection
• implement Graph Cut Segmentation, Sliding Window Detection, HOG
• implement the forward pass of the convolution net, max pooling and dense layers, plus the relu activation function
• implement self-attention, transformer, ViT model
• implement Harris detector, matching, fundamental matrix estimation, RANSAC