🧑‍🏫 This section is prepared by: Bao Guo (CE)

🗓️ Latest Update Date: 15th March 2025 (Released)

🔹 What is Object Detection?

Object detection is a computer vision technology that identifies and locates objects within images or videos, enabling machines to interpret visual data.

1. Combines Classification & Localization: It not only recognizes object categories (e.g., "car" or "person") but also pinpoints their positions using bounding boxes.
2. Key Applications: Powers autonomous vehicles, surveillance systems, and retail analytics (e.g., pedestrian detection, inventory tracking).
3. Advancements in AI: Modern techniques like YOLO, Faster R-CNN, and transformer-based models (e.g., DETR) enhance speed and accuracy through deep learning.

In this workshop, we will learn how to:

1. Workflow and Key tools to achieve Object Detection
2. Implement a pre-trained / self-trained model (YOLO) to detect objects in real-time.
3. Training a model

🔹 1. Setting Up the Development Environment 🖥️

🔹 2. Quick Start 🔰

🔹 3. YOLO Dataset Collection

🔹 4. Purpose and Concept of Training