Attrasoft ImageDeepLearner is a deep learning developer tool for image matching.

You do not need any domain knowledge to use this software. This software can be used in the following fields:

• Image recognition, identification, and classification;

• Machine learning;

• Computer vision;

• AI;

• . . .

• ImageDeepLearner User's Guide

• Video Guide

Title	Contents
1. End Results	This first video will show what the end resulting software will look like and we will show how it identifies images. In the next several videos, we will go through the User's Guide.
2. What is Deep Learning?	This video will explain what Deep Learning is. In the next several videos, we will go through the User's Guide.
3. Data Preparation	This video will explain how the data preparation works using the Attrasoft ImageDeepLearner software. The preparation work includes: Data for feature generation; Data for teaching the software what is an image match; Data for testing the software; Data for saving software generated data.
4. Feature Extraction	This video will explain how the Feature Extraction Layers work using the Attrasoft ImageDeepLearner software.
5. Generating Variation	This video will explain how to obtain image variations for supervised learning using the Attrasoft ImageDeepLearner software.
6. Supervised Learning	This video will explain how the supervised learning layer works.
7. Training & Retraining	This video will continue to explain how the supervised learning layer works.
8. Testing	This video will explain how to test the trained ImageDeepLearner software.
9. Redistribution Software	This video will explain how to generate Redistribution Software.
10. Four Layers	This video will explain how the four layer deep learning architecture identifies concepts.
11. Segment Features	This video will explain how to get features from image segments.
12. Features From Features	This video will explain how to get upper-layer features from lower-layer features.
13. Four-layer Supervised Learning	This video will explain how four-layer supervised learning works.
14. Four-layer Testing	This video, I will explain how to test a trained ImageDeepLearner software.
15. Four-layer Redistribution Software	This video will explain how to generate Redistribution Software for the four-layer architecture.
16. Five Layers	This video will explain how the five-layer deep learning architecture identifies concepts.
17. Five-Layer Segment Features	This video will explain how to get features from image segments in the five-layer deep learning architecture.
18. Five-Layer Features From Features	This video will explain how to get upper-layer features from lower-layer features in the five-layer deep learning architecture.
19. Supervised Learning, Testing, Redistribution	This video will explain how supervised learning works, how to test a trained ImageDeepLearner software, & how to generate Redistribution Software for the five-layer architecture.

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