This page outlines the weekly schedule for lectures, labs, assignments, and examinations. The schedule will be updated regularly to align with the University of Juba's academic calendar and holiday schedule. Reading materials, lecture slides, and lab materials will be accessible through this schedule, with links provided for downloading prior to the commencement of each lecture or lab session. If you encounter any difficulties or have questions, please contact the lead Teaching Fellow, Thiong Abraham.

Week 4

March 25th and 27th, 2025

Object Detection

This lecture introduces object detection, a computer vision task that extends beyond image classification by not only identifying the objects present in an image but also locating their spatial extent through bounding boxes. Building upon the foundational concepts of image classification, where a model learns to assign a single label to an entire image, object detection models learn to simultaneously classify and localize multiple objects. We'll explore techniques like sliding windows, region proposal networks, and modern architectures such as YOLO and Faster R-CNN, detailing how these methods utilize convolutional neural networks to extract features, predict object classes, and refine bounding box coordinates. The lecture will also cover evaluation metrics like mean Average Precision (mAP) and practical applications of object detection, from autonomous driving to industrial automation.

Lecture
Slides: TBD
Overview of Object Detection
Algorithms for Object Detection
Yolov11 for Object Detection
Laboratory
Using YOLOv11 to detect objects
TBD
Assignment
Due March 28th
Week 4 Status Report - Click here to submit...

Week 3

March 18th and 20th, 2025

Image Classification

This lecture introduces Vision Transformers (ViTs), a cutting-edge approach to image classification that leverages the power of transformer architectures, originally developed for natural language processing, to analyze visual data. The session will cover the fundamental principles of Vision Transformers, including their architecture, self-attention mechanisms, and how they differ from traditional convolutional neural networks (CNNs). We will explore the advantages of ViTs, such as their ability to capture global context and their scalability to large datasets, as well as their challenges, including computational requirements and data efficiency.

Lecture
Continuation of Image Classification
Overview of Vision Transformer
Details of Attention Mechanism in Transformers
Laboratory
Finetuning a Vision Transformer for Detecting Disease in Bean Leaves (i.e based on a leaf image, the goal of this task is to predict the disease type: Angular Leaf Spot and Bean Rust, if any.)
Assignment
Due March 14th
Week 3 Status Report - Due March 21, 2025 - Click here to submit...

Week 2

March 11th and 13th, 2025

Image Classification

This lecture provides a comprehensive introduction to image classification, a core computer vision task, beginning with an overview of its fundamental principles and diverse applications. The session delves into the algorithmic foundations, highlighting the pivotal role of Convolutional Neural Networks (CNNs) in learning hierarchical image features. Various CNN architectures, including ResNet, VGG, and Inception, are explored, emphasizing their unique strengths and design considerations. The lecture culminates in a hands-on lab exercise where participants apply their newfound knowledge to classify African wildlife images, utilizing a provided dataset and pre-trained models. This practical component allows students to solidify their understanding of CNNs and their application in real-world scenarios, specifically focusing on the identification of species like buffalo, elephant, rhino, and zebra, thereby bridging theoretical concepts with practical implementation.

Lecture
Overview of Image Classification
Refresh of Convolutional Neural Networks
CNN Architectures
Laboratory
Finetuning ResNet for African Wildlife Classification
Assignment
Due March 14th
Week 2 Status Report - Click here...

Week 1

March 4th and 6th, 2025

Introduction and Logistics

This module introduces the course materials to students and gives an overview of Computer Vision, its tasks, applications, and the state of the art.

Lecture
Course Overview and Logistics
Overview of Computer Vision
Laboratory
Introduction to Google Colab and Python for computer vision
Assignment
Due March 4th
Week 1 Status Report - Due March 9th, 2024 Click here...
Complete assignment 1 if you have not already done so - Click here...
Create a Gemini account if you don't already have one - Click here...
Create a ChatGPT account if you don't already have one - Click here...
Create a Deepseek account if you don't already have one - Click here...