American Journal of Neural Networks and Applications

Volume 6, Issue 2, December 2020

  • Urdu Nastaleeq Nib Calligraphy Pattern Recognition

    Mateen Ahmed Abbasi, Naila Fareen, Adnan Ahmed Abbasi

    Issue: Volume 6, Issue 2, December 2020
    Pages: 16-21
    Received: 31 March 2020
    Accepted: 10 April 2020
    Published: 27 August 2020
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    Abstract: Nib calligraphy pattern recognition is the way to convert handwritten nib font into its equivalent machine understandable or readable form. Nib calligraphy pattern recognition is derived from pattern recognition and computer vision, a variety of work has been done on Urdu literature and on Urdu handwritten automatic line segmentation. This research... Show More
  • Overview of the Three-dimensional Convolutional Neural Networks Usage in Medical Computer-aided Diagnosis Systems

    Bohdan Chapaliuk

    Issue: Volume 6, Issue 2, December 2020
    Pages: 22-28
    Received: 4 August 2020
    Accepted: 17 August 2020
    Published: 27 August 2020
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    Abstract: Medical computer-aided diagnosis systems are essential applications that help doctors speed up, standardize, and improve disease prediction quality. Nevertheless, it is hard to implement a high-accuracy diagnosis system due to complex medical data structures that are hard to interpret even by an experienced radiologist, lack of the labeled data, an... Show More
  • A Neural Network Approach to Writer’s Model for Full Likelihood Ratio in Handwriting Analysis

    Abiodun Adeyinka Oluwabusayo, Adeyemo Adesesan Barnabas

    Issue: Volume 6, Issue 2, December 2020
    Pages: 29-35
    Received: 4 November 2020
    Accepted: 2 December 2020
    Published: 16 December 2020
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    Abstract: Handwriting is an integral part of our life that can predict who we are because the style of writing is unique for every person. Handwriting is also a key element in document examination as it leaves a forensic document examiner with the task of determining who the writer of a particular document is and this is achieved through the likelihood ratio... Show More