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First, scene text detection

1. The mainstream framework for scene text detection and the mainstream approach at each stage

2. Application of deep learning in scene text detection: End to end icpr2012 text spotting eccv2014

Principle and implementation of 3.SWT algorithm (i) Stroke width transformation

Principle and implementation of 4.SWT algorithm (ii) connected domain marker (BFS,DFS)

Introduction to 5.MSER algorithm and vlfeat OPENCV usage

6. Implementation of text line connection algorithm

Second, deep learning/machine learning principles, the use of the framework

1. Training Lenet

2. Own data Training charnet

3. CS231N Series

4. Caffe Principle Series

5. Cross-validation

6. Decision Tree

7. Punitive regularization L0 L1 L2

8. Deeplearning Book

9. Random Forest

Third, the algorithm

1 hash principle and simple hash implementation

2 Leetcode Wordpattern

3 Sudoku Calculator + Sudoku Game

4. Array, linked list

5. Joseph Ring

6. Traversal of the tree

Iv. calculation and visual other

1. Features of image retrieval bow, VLAD, deep feature, and demo

2. The establishment of inverted index in large-scale image retrieval

3. TLD Optical Flow method

V. Reading and practice of the thesis

1.Text Detection and recognition in Imagery:a Survey

2. rccnn

3. FCN

4. lstm

Vi. Other computer fields

Linux use

Git uses

Seven, Daily

Need to tidy up the blog