Tutorials & Insights

Thoughtful guides to help you get the most out of AIOZ AI R&D. Created and curated by the AIOZ AI team.

Decentralized AI

Take AIOZ AI Network from zero to production.
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1. Intelligent Agents in AIOZ Network

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2. Introduction to Federated Learning.

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3. Network Sytem and data silos for Federated Learning.

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4. Topologies in Decentralized Federated Learning.

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5. Smart Routing.

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6. AI-driven routing (part 1) Centralized Routing.

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7. AI-driven routing (part 2) Decentralize Routing.

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8. AI-driven routing (part 3) Hybrid Routing.

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9. AI-driven routing (part 4) Smart Routing Effectiveness.

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10. AI-driven routing (part 5) Challenges and Open Issues.

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11. Smart Caching.

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12. Smart Transcoding (part 1) Introduction.

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13. Smart Transcoding (part 2) Video Transcoding and Delivery with Blockchain.

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14. Smart Transcoding (part 3) Three-stage STACKELBERG game.

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15. Smart Transcoding (part 4) Effectiveness Evaluation.

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16. Video Compression (Part 1)

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17. Video Compression (Part 2)

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18. Decentralized Federated Learning and Research Directions (Part 1).

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19. Decentralized Federated Learning and Research Directions (Part 2).

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20. Foundation Model and Federated Learning (part 1).

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21. Foundation Model and Federated Learning (Part 2).

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Computer Vision

If We Want Machines to Think, We Need to Teach Them to See.
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6. Video recognition and categorization (Part 1 - Introduction)

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7. Video recognition and categorization (Part 2 - Datasets and Evaluate Metrics)

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8. Video recognition and categorization (Part 3 - Applying RNN)

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9. Video recognition and categorization (Part 4 - Applying Deep Learning)

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10. Video recognition and categorization (Part 5 - Applying Deep Learning (cont.))

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11. Video recognition and categorization (Part 6 - A basic tutorial)

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13. Representation Learning

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14. Abnormal Human Activity Recognition (Part 1 - Introduction)

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15. Relationship between energy map and seam carving

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16. Abnormal Human Activity Recognition (Part 2 - Two-Dimensional AbHAR)

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18. Abnormal Human Activity Recognition (Part 3 - Two-Dimensional AbHAR (cont.))

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19. Abnormal Human Activity Recognition (Part 4 - Three-Dimensional AbHAR)

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21. Abnormal Human Activity Recognition (Part 5 - Three-Dimensional AbHAR) (cont.)

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24. Abnormal Human Activity Recognition (Part 6 - Three-Dimensional AbHAR) (cont.)

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25. Abnormal Human Activity Recognition (Part 7 - Deep features based action description)

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29. Abnormal Human Activity Recognition (Part 8 - Deep features based action description)

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36. Abnormal Human Activity Recognition (Part 9 - Discussion)

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45. Abnormal Human Activity Recognition (Part 10 - Datasets)

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46. Abnormal Human Activity Recognition (Part 11 - Overall Summary)

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Robotics

A layman, with a fleeting understanding of technology, would link it to robots.

Computer Graphics

If it looks like computer graphics, it is not good computer graphics.
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23. DanceNet for Music-driven Dance Generation

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24. Music to Multi-People Dance Synthesis with Style Collaboration.

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25. Method comparison between three latest Dance Generation approaches.

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26. Music2Dance and GroupDancer comparison.

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27. 3D Downstream Tasks for Foundation Model (Part 1)

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27. 3D Downstream Tasks for Foundation Model (Part 2).

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29. 3D Downstream Tasks for Foundation Model (Part 1).

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30. 3D Downstream Tasks for Foundation Model (Part2).

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31. 3D Downstream Tasks for Foundation Model (Part 1).

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Medical Image Processing

The flashiest use of medical AI is to perform tasks that even the best human providers cannot yet do.

Machine Learning Operations (MLOps)

MLOps is the natural progression of DevOps in the context of AI.