Yes, several excellent books provide comprehensive insights into computer vision, catering to different expertise levels. For beginners, Learning OpenCV 4 by Adrian Kaehler and Gary Bradski is a great starting point. It introduces practical applications and hands-on projects using the OpenCV library. For a more theoretical approach, Computer Vision: Algorithms and Applications by Richard Szeliski is a widely recommended textbook that covers fundamental concepts and algorithms in computer vision. Advanced learners can explore Deep Learning for Computer Vision by Rajalingappaa Shanmugamani or Deep Learning for Vision Systems by Mohamed Elgendy, which focus on using deep learning frameworks like TensorFlow and PyTorch for computer vision tasks. These books not only explain the underlying principles but also provide practical examples, making them valuable resources for students, researchers, and professionals.
Is there any good books on computer vision?
- AI & Machine Learning
- Master Video AI
- Getting Started with Milvus
- Advanced Techniques in Vector Database Management
- GenAI Ecosystem
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
What is a common architecture used in few-shot learning?
A common architecture used in few-shot learning is the Siamese Network. This architecture consists of two identical subn
What is the difference between discrete and continuous diffusion models?
Discrete and continuous diffusion models are two approaches used to describe how information, materials, or phenomena sp
What are the steps to fine-tune a Sentence Transformer using a triplet loss or contrastive loss objective?
To fine-tune a Sentence Transformer using triplet loss or contrastive loss, follow these structured steps:
**1. Prepare