Search Results - (( developing formative perceptions algorithm ) OR ( java implementation matching algorithm ))

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  1. 1
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  2. 2
    Multi-floor indoor location estimation system based on wireless local area network

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…During location estimation, current histogram of RSS at unknown location will be compared to the database. The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. …”
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  3. 3
    Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan

    Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan by Sa'dan, Siti 'Aisyah

    Published 2009
    “…The scope of this project is digital image of beach photographs with JPegs format. This project is implemented using a basic KMeans clustering as the algorithm for color segmentation and using direct technique to annotate the colors with the appropriate words by using predefined colors.…”
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  4. 4
    An Agent-Based System with Personalization and Intelligent Assistance Services for Facilitating Knowledge Sharing

    An Agent-Based System with Personalization and Intelligent Assistance Services for Facilitating Knowledge Sharing by Mohd Sharef, Nurfadhlina

    Published 2006
    “…KSFaci is embedded in web environment and is implemented using Java Servlet and runs under Apache server. …”
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  5. 5
    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal

    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal by Camellia , Mohd Kamal

    Published 2004
    “…For the Feed Forward, Recurrent and Self Organizing Map Networks there are the Neuron Model, Basic Architecture and Training Algorithm. The demonstrations are included each every topic. …”
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  6. 6
    Deep reinforcement learning-based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehicles

    Deep reinforcement learning-based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehicles by Abu Jafar, Md Muzahid, Syafiq Fauzi, Kamarulzaman, Rahman, Md. Arafatur, Alenezi, Ali H.

    Published 2022
    “…A perception network structure based on formation and on actor-critic methodologies is employed to enhance the decision-making process. …”
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  7. 7
    Deep reinforcement learning based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehicles

    Deep reinforcement learning based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehicles by Abu Jafar, Md Muzahid, Syafiq Fauzi, Kamarulzaman, Rahman, Md. Arafatur, Alenezi, Ali H.

    Published 2022
    “…A perception network structure based on formation and on actor-critic methodologies is employed to enhance the decision-making process. …”
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  8. 8
    Cooperative heterogeneous vehicular clustering for road traffic management / Iftikhar Ahmad

    Cooperative heterogeneous vehicular clustering for road traffic management / Iftikhar Ahmad by Iftikhar , Ahmad

    Published 2019
    “…Furthermore, a self-location calculation algorithm is developed to enable vehicles to calculate their location in the absence of global positioning system (GPS) signals. …”
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  9. 9
    Zero distortion-based steganography for handwritten signature

    Zero distortion-based steganography for handwritten signature by Iranmanesh, Vahab

    Published 2018
    “…This means that any changes on the cover media (c) could lead to the identification of the stego media (s), which contains the secret message (m). Thus, developing a steganographic algorithm to use cover media (c) without raising attention is the most challenging task in data hiding. …”
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