CityScapes – Object Detection

This project utilizes the YOLOv7 model to perform object detection task on Cityscapes dataset. The cityscapes dataset is a large-scale dataset that stands as one of the standard advanced driver-assistance system (ADAS) benchmarks for multiple vision-related tasks.

Cifar10 – Resnet

This project implements the resnet algorithm using CIFAR-10 dataset for image classification tasks.

SQuAD – Albert

This project implements the Albert algorithm using the SQuAD (Stanford Question Answering Dataset) for question answering tasks.

Domain Gap

This project addresses a domain gap between KITTI and Cityscapes datasets for semantic segmentation in autonomous driving scenarios. By applying domain adaptation techniques and designing a robust model, we aim to improve cross-dataset generalization. The project seeks to enhance the model’s real-world applicability and contribute to advancements in domain adaptation research.