Face Recognition Using Artificial Neural Network Group-Based Adaptive Tolerance (GAT) Trees  

Oleh:

Fulcher, J. ; Zhang, Ming

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 7 no. 3 (1996), page 555-567.
Topik: neural network; face recognition; artificial neural networks; group - based adaptive tolerance (GAT) trees

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.1 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Recent artificial neural network research has focused on simple models, but such models have not been very successful in describing complex systems (such as face recognition). This paper introduces the artificial neural network group - based adaptive tolerance (GAT) tree model for translation-invariant face recognition, suitable for use in an airport security system. GAT trees use a two - stage divide - and - conquer tree - type approach. The first stage determines general properties of the input, such as whether the facial image contains glasses or a beard. The second stage identifies the individual. Face perception classification, detection of front faces with glasses and / or beards, and face recognition results using GAT trees under laboratory conditions are presented. We conclude that the neural network group - based model offers significant improvement over conventional neural network trees for this task.

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