Computer-Vision-With-Deep-Learning

4th Year Computer Engineering Course at Queen's University

Labs

Lab 1: Denoising Autoencoder

• Objective: Learn how to build and train a denoising autoencoder to remove noise from images.

Lab 2: Neural Style Transfer with AdaIN

• Objective: Implement the AdaIN technique to transfer artistic styles from one image to another.

Lab 3: CIFAR-100 Image Classification

• Objective: Develop a model to classify images from the CIFAR-100 dataset.
• Key Concepts: CNNs, Data Augmentation, Transfer Learning.

Lab 4: YOLO Object Detection with Anchors

• Objective: Utilize YOLO (You Only Look Once) algorithm for real-time object detection.
• Key Concepts: Object Detection, Real-time Processing.

Lab 5: Pet Nose Localization

• Objective: Create a model to accurately locate the noses of pets in images.
• Application: Understanding of Localization in Computer Vision.