Tutorials on RGB-D (color and depth) image segmentation can be found on platforms like Medium, YouTube, and GitHub. Specific resources include research-oriented blogs on Towards Data Science and video tutorials on channels like StatQuest or Deeplearning.ai. Framework documentation, such as PyTorch and TensorFlow, often includes examples of semantic segmentation that can be adapted for RGB-D data. For advanced learners, papers with code repositories (https://paperswithcode.com/) provide cutting-edge implementations. Exploring datasets like NYU Depth V2 or SUN RGB-D will also help you practice and apply segmentation techniques.
Where can I find tutorials about RGB-D image segmentation?
- GenAI Ecosystem
- Mastering Audio AI
- Accelerated Vector Search
- Master Video AI
- Optimizing Your RAG Applications: Strategies and Methods
- 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
How can voice commands be integrated into AR experiences?
Integrating voice commands into augmented reality (AR) experiences involves using voice recognition technology to allow
How do SSL models handle class imbalance during training?
SSL (Semi-Supervised Learning) models manage class imbalance during training using various strategies that help ensure b
How do embeddings support multi-modal AI models?
Embeddings play a crucial role in supporting multi-modal AI models by providing a way to represent different types of da