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אקדמי בכיר

Case Study

Fine Writing Style Classification Using Siamese Neural Network

Alaa Abdalhaleem, Berat Kurar Barakat, Jihad El-Sana

This paper presents an automatic system for dividing a manuscript into similar parts, according to their similarity in writing style. This system is based on Siamese neural network, which consists of two identical sub-networks joined at their outputs. In the training the two sub-networks extract features from two patches, while the joining neuron measures the distance between the two feature vectors. Patches from the same page are considered as identical and patches from different books are considered as different. Based on that, the Siamese network computes the distances between patches of the same book.

שפת פרסום אנגלית
דפים 62-66
סטטוס פרסום פורסם - 02.10.2018
8480212

Keywords

Deep-learning
Siamese-network
Supervised-learning
Writer-identification
Writing-style

ASJC Scopus subject areas

Signal Processing
Linguistics and Language
Computer Vision and Pattern Recognition
גישה למסמך
10.1109/ASAR.2018.8480212
קבצים וקישורים אחרים
Link to publication in Scopus