Search Results - (( frames detection selection algorithm ) OR ( java application optimization algorithm ))

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  1. 1
    An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization

    An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization by Mizher, Manar Abduljabbar Ahmad, Ang, Mei Choo, Sheikh Abdullah, Siti Norul Huda, Kok, Weng Ng

    Published 2019
    “…The objective of this work is to improve our previous action key frames extraction algorithm (AKF) by adapting a threshold which selects action key frames as final key frames. …”
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  2. 2
    Video surveillance: Item monitoring against theft

    Video surveillance: Item monitoring against theft by Chong, Yiing Sheah

    Published 2023
    “…After that, the system will get the current frame to find the common features with the background frame by using a feature matching algorithm. …”
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  3. 3
    Automated threshold detection for object segmentation in colour image

    Automated threshold detection for object segmentation in colour image by Akhtaruzzaman, Md., Shafie, Amir Akramin, Khan, Md. Raisuddin

    Published 2016
    “…The procedure starts with selection of optimal RGB channel. Then H(•) algorithm is applied for automated threshold detection to convert the image frames into grayscale image. …”
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  4. 4
    Vehicle speed detection using frame differencing for smart surveillance system

    Vehicle speed detection using frame differencing for smart surveillance system by Hasliza, A. Rahim@Samsuddin, Usman Ullah, Sheikh, Dr., R. Badlishah, Ahmad, Prof. Madya Dr., Aini Syuhada, Md Zain, Wan Nur Suryani Firuz, Wan Ariffin

    Published 2011
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  5. 5
    Fast shot boundary detection based on separable moments and support vector machine

    Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

    Published 2021
    “…First, for each frame, the active area is selected such that only the informative content is considered. …”
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  6. 6
    Optimum Colour Space Selection for Ulcerated Regions using Statistical Analysis and Classification of Ulcerated Frames from WCE Video Footage

    Optimum Colour Space Selection for Ulcerated Regions using Statistical Analysis and Classification of Ulcerated Frames from WCE Video Footage by Suman, Shipra, Hussin, Fawnizu Azmadi, Nicolas, Walter, Malik, Aamir Saeed, Goh, Khean Lee, Hilmi, Ida, Ho, Shaiw Hooi

    Published 2015
    “…This paper proposes an ulcerated frame detection method based on RGB and CIE Lab colour spaces. …”
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  7. 7
    Optimum Colour Space Selection for Ulcerated Regions Using Statistical Analysis and Classification of Ulcerated Frames from WCE Video Footage

    Optimum Colour Space Selection for Ulcerated Regions Using Statistical Analysis and Classification of Ulcerated Frames from WCE Video Footage by Suman, Shipra, Nicolas, Walter, Hussin, Fawnizu Azmadi, Malik, Aamir Saeed, Ho, Shiaw Hooi, Goh, Khean Lee, Hilmi, Ida

    Published 2015
    “…This paper proposes an ulcerated frame detection method based on RGB and CIE Lab colour spaces. …”
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  8. 8
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  9. 9
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  10. 10
    Automatic detection of the end-diastolic and end-systolic from 4D echocardiographics images

    Automatic detection of the end-diastolic and end-systolic from 4D echocardiographics images by Abboud, Anas A., O. K. Rahmat, Rahmita Wirza, Kadiman, Suhaini, Dimon, Mohd Zamrin, Abdullah, Lili Nurliyana, Saripan, M. Iqbal, Khaleel, Hasan Hadi

    Published 2015
    “…By computing the area of three slices along one cardiac cycle and selecting the maximum area as the ED frame and the minimum area as the ES frame. …”
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  11. 11
    Identifying and detecting unlawful behavior in video images using genetic algorithm / Shahirah Mohamed Hatim

    Identifying and detecting unlawful behavior in video images using genetic algorithm / Shahirah Mohamed Hatim by Mohamed Hatim, Shahirah

    Published 2016
    “…Video scenes are sequence of picture frame. The focus of this research is to identify and detect unlawful behavior in an academic restricted area. …”
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  12. 12
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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  13. 13
    A fuzzy approach for early human action detection / Ekta Vats

    A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

    Published 2016
    “…In order to perform early human action detection, the conventional classification problem is modified into frame-by-frame level classification. …”
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  14. 14
    Moving detection using cellular neural network (CNN)

    Moving detection using cellular neural network (CNN) by Prema Latha, Subramaniam

    Published 2008
    “…The video then are segmented into images using SC Video Developer. Ten images are selected to be used in this project. The algorithm created is used to detect the ball in the images. …”
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  15. 15
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…Furthermore, colour threshold analysis and edge detection algorithms are redesigned exclusively to refine the two-dimensional coefficients into a more meaningful low-level representation. …”
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  16. 16
    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
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  17. 17
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  18. 18
    Frame selection based on modified entropy and object motion for secured data hiding in videos

    Frame selection based on modified entropy and object motion for secured data hiding in videos by Muhammad Fuad, Abdullah

    Published 2021
    “…The proposed frame selections provided additional security where the hidden data were difficult to be detected. …”
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  19. 19
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
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  20. 20
    Passive Client-Centric Rogue Access Point Detection Framework For WiFi Hotspots

    Passive Client-Centric Rogue Access Point Detection Framework For WiFi Hotspots by Ahmad, Nazrul Muhaimin

    Published 2018
    “…The proliferation of Wi-Fi hotspots in public places provides seamless Internet connectivity anywhere at any time to the wireless clients.Although many hotspots are often unprotected,unmanaged and unencrypted,this does not prevent the clients from actively connecting to the network.The underlying problem is that the network Access Point (AP) is always trusted.The adversary can impersonate a legitimate AP by setting up a rogue AP to commit espionage and to launch evil-twin attack,session hijacking,and eavesdropping.To aggravate the threats, existing detection solutions are ill-equipped to safeguard the client against rogue AP.Infrastructure- centric solutions are heavily relied on the deployment of sensors or centralized server for rogue AP detection, which are limited,expensive and rarely to be implemented in hotspots.Even though client-centric solutions offer threat-aware protection for the client,but the dependency of the existing solutions on the spoofable contextual network information and the necessity to be associated with the network makes those solutions are not viable for the hotspot’s client.Hence,this work proposes a framework of passive client-centric rogue AP detection for hotspots.Unlike existing solutions,the key idea is to piggyback AP-specific and network-specific information in IEEE 802.11 beacon frame that enables the client to perform the detection without authentication and association to any AP.Based on the spatial fingerprints included in the broadcasted information from the APs in the vicinity of the client,this work discloses a novel concept that enables the rogue AP detection via the client’s ability to self-colocalize and self-validate its own position in the hotspot.The legitimacy of the APs in the hotspot,in this view,lies in the fact that the correct matching between the Received Signal Strength Indicator (RSSI) measurements at the client and pre-recorded fingerprints is attainable when the beacons are transmitted only from the legitimate APs.Hence,any anomalousness in AP’s beacon frame or any attempt to replay the legitimate AP’s beacon frame from different location can be detected and classified as rogue AP threats.Through experiments in real environment,the results demonstrate that with proper algorithm selection and parameters tuning,the rogue AP detection framework can achieve over 90% detection accuracy in classifying the absence and presence of rogue AP threats in the hotspot.…”
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