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Wyszukujesz frazę "Ahmed, Nisar" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Electronic Toll Collector Framework
Autorzy:
Mujeeb, Abdul
Ahmed, Nisar
Arshed, Husnain
Khan, Farhan Ajmal
Powiązania:
https://bibliotekanauki.pl/articles/2022366.pdf
Data publikacji:
2022
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
electronic toll collector
TensorFlow
Yolov2
image classification
analytics
centralized system
Opis:
Manual toll collection systems are obsolete due to time, fuel, and pollution issues and need to be replaced by new and better alternatives. Traditionally, governments have always employed people to collect toll, but the manual labor isn’t much effective when it comes to monitoring and efficiency. We took this problem and researched out an effective solution i.e., “Electronic Toll Collector Framework” which is a framework mainly for collection and monitoring of the toll fees collected by the toll plazas in the vicinity of metropolitan cities like Lahore or Karachi. The software can generate toll tax based on vehicle type. Additionally, it can also generate daily/monthly/yearly revenue reports. The framework can serve other purposes like monitoring of vehicles (by the law enforcement agencies) and generation of analytics. It can also serve as a backbone for the government departments who are having a hard time monitoring the revenue generated by the employers. There are two operational modes of the framework (partly manual and automatic). The partly manual approach uses TensorFlow backend, and the automatic approach uses Yolov2 backend. This work will be helpful in guiding future research and practical work in this domain.
Źródło:
Advances in Science and Technology. Research Journal; 2022, 16, 1; 294-302
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Face Recognition Comparative Analysis Using Different Machine Learning Approaches
Autorzy:
Ahmed, Nisar
Khan, Farhan Ajmal
Ullah, Zain
Ahmed, Hasnain
Shahzad, Taimur
Ali, Nableela
Powiązania:
https://bibliotekanauki.pl/articles/2024199.pdf
Data publikacji:
2021
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
linear discriminant analysis
k-nearest neighbor
support vector machine
principal component analysis
liniowa analiza dyskryminacyjna
maszyna wektorów podporowych
analiza głównych składowych
Opis:
The problem of a facial biometrics system was discussed in this research, in which different classifiers were used within the framework of face recognition. Different similarity measures exist to solve the performance of facial recognition problems. Here, four machine learning approaches were considered, namely, K-nearest neighbor (KNN), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Principal Component Analysis (PCA). The usefulness of multiple classification systems was also seen and evaluated in terms of their ability to correctly classify a face. A combination of multiple algorithms such as PCA+1NN, LDA+1NN, PCA+ LDA+1NN, SVM, and SVM+PCA was used. All of them performed with exceptional values of above 90% but PCA+LDA+1N scored the highest average accuracy, i.e. 98%.
Źródło:
Advances in Science and Technology. Research Journal; 2021, 15, 1; 265-272
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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