2.4 Normalization
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

2.1 Structure 
2.2 Filters 
2.3 Processing 
2.4 Normalization 
2.5 Signature 
2.6 Segment Matching 
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2.4   Normalization

The Normalization Sub-Layer will prepare the images for the underlying image matching engine. The Attrasoft Image Matching Engine is an internally developed algorithm, which is called the “Attrasoft Boltzmann Machine” or ABM. The ABM neural net deployed in the ImageFinder, by default, is a 100x100 array of neurons.

While any size of neural net can be used, when coming to a particular application, a decision has to be made. The ImageFinder uses 6 different sizes:

  •    10,000 neurons,
  •    8,100 neurons,
  •    6,400 neurons,
  •    4,900 neurons, or
  •    2,500 neurons.

Later in the multi-layered design, the number of neurons can be much larger. The Reduction Filter will connect the images to various sets of ABM neural networks.

[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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