Abstract
Computer Vision offers meaningful solutions in everyday life such as becoming the eyes of blind people, traffic control, cashier-free stores, autonomous vehicles, and delivery robots.
With this book, we seek to share our expertise with anyone motivated to explore and make meaningful contributions to the field of Computer Vision.
This book is for anyone who wants to explore the field of Computer Vision, especially those who feel they lack a strong theoretical background in deep learning or image processing. We have been on the same journey as you—we understand the excitement, confusion, and technical challenges you may be facing. This book is designed to make your learning journey smoother, more structured, and truly enjoyable.
We truly believe that with the guidance provided in this book, everyone can develop and implement powerful Computer Vision models—no matter their starting point!
In addition to simplifying the foundations, we also highlight recent trends such as multimodal learning—where vision is combined with text, audio, or tabular data—and the importance of staying current with cutting-edge architectures like YOLOv12, which was released just a month ago. We designed it to be beneficial for readers from beginner to advanced levels.
The book begins with a brief overview of core concepts in Convolutional Neural Networks (CNNs) and Computer Vision, followed by step-by-step Python implementations using Jupyter Notebooks. All notebooks are organised in folders matching the chapter numbers, and each notebook is accompanied by detailed explanations under the relevant code blocks. You can access all materials via QR codes on the next page, which link directly to our GitHub repository and website.
With this book, we seek to share our expertise with anyone motivated to explore and make meaningful contributions to the field of Computer Vision.
This book is for anyone who wants to explore the field of Computer Vision, especially those who feel they lack a strong theoretical background in deep learning or image processing. We have been on the same journey as you—we understand the excitement, confusion, and technical challenges you may be facing. This book is designed to make your learning journey smoother, more structured, and truly enjoyable.
We truly believe that with the guidance provided in this book, everyone can develop and implement powerful Computer Vision models—no matter their starting point!
In addition to simplifying the foundations, we also highlight recent trends such as multimodal learning—where vision is combined with text, audio, or tabular data—and the importance of staying current with cutting-edge architectures like YOLOv12, which was released just a month ago. We designed it to be beneficial for readers from beginner to advanced levels.
The book begins with a brief overview of core concepts in Convolutional Neural Networks (CNNs) and Computer Vision, followed by step-by-step Python implementations using Jupyter Notebooks. All notebooks are organised in folders matching the chapter numbers, and each notebook is accompanied by detailed explanations under the relevant code blocks. You can access all materials via QR codes on the next page, which link directly to our GitHub repository and website.
| Original language | English |
|---|---|
| Publisher | Independently Published |
| Number of pages | 293 |
| ISBN (Print) | 979-8317445508 |
| Publication status | Published - 10 Apr 2025 |
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