15 NeuralFilters
About1 Introduction2 Image Recognition3 TransApplet4 API5 Interface6 Input7 Image Display8 Preprocessing9 Processing10 Normalization11 Parameter Class12 Image Signatures13 Unsupervised Filters14 BioFilters15 NeuralFilters16 Dynamic Library17 NeuralNet Filter18 Parameters19 Input Options20 Database Input21 Video Input22  Live Video Input23  Counting & Tracking24  Counting 25  Batch Job26 ImageFinder for DOS27 ImageHunt 28 Support Packages

15.1 NeuralFilter Menu 
15.2 NeuralFilter API 
15.3 Parameters 
15.4 Training Design 
15.5 Implementation 
15.6 N:N Design 
15.7 N:N Implementation 
15.8 1:N Design 
15.9 1:N Implementation 
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15.   NeuralFilters

The NeuralFilter matches two whole images, which is similar to the BioFilter. The NeuralFilter is better than both Unsupervised Filter and BioFilter, but it requires a large amount of training data. Training data teaches the NeuralFilter who should match with whom. In comparison to early filters:

  •    The advantage of the NeuralFilter is that it is more accurate.
  •    The disadvantage of the NeuralFilter is that it requires more training data than the BioFilter.

The chapter project is located at:


The executable file is located at:


We also call this folder “.\”. That is, “.\” is “c:\transapplet70\imagefinder\bin\Release\”. The data is located at: “.\ex_label” or “c:\transapplet70\imagefinder\bin\Release\ ex_label”.


[Home][About][1 Introduction][2 Image Recognition][3 TransApplet][4 API][5 Interface][6 Input][7 Image Display][8 Preprocessing][9 Processing][10 Normalization][11 Parameter Class][12 Image Signatures][13 Unsupervised Filters][14 BioFilters][15 NeuralFilters][16 Dynamic Library][17 NeuralNet Filter][18 Parameters][19 Input Options][20 Database Input][21 Video Input][22 Live Video Input][23 Counting & Tracking][24 Counting ][25 Batch Job][26 ImageFinder for DOS][27 ImageHunt ][28 Support Packages]

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