Search Results - (( robust features selection algorithm ) OR ( java application using algorithm ))

Cancellable face template algorithm based on speeded-up robust features and winner-takes-all by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This research presents a cancell able face image algorithm built upon the speeded-up robust features method to extract and select features. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…These results are essential for future work direction in designing a robust unsupervised feature selection based on LDA.…”
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Impact of Balanced Exploration and Exploitation on High-dimensional Feature Selection with Hierarchical Whale Optimisation Algorithm by Yab, Li Yu, Wahid, Noorhaniza, A Hamid, Rahayu

“…Hence, this study introduced the Hierarchical Whale Optimisation Algorithm (HiWOA), an approach designed to enhance the WOA’s stability and performance in HDD feature selection tasks. …”
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Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

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Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

“…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Multilocal feature selection using genetic algorithm for face identification by Mohamad, Dzulkifli

“…This paper presents an improved offline face recognition algorithm based on a multi-local feature selection approach for grayscale images. …”
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Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

“…Such automated systems must rely on robust and effective algorithms for detection and prediction. …”
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Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.] by Afolabi, Akindele Segun, Akinola, Olubunmi Adewale, Odetoye, Oyinlolu Ayomidotun, Adetiba, Emmanuel

“…Hence, it is crucial to determine ML models that are robust against such disruptions. In this paper, three algorithms were developed: the first was for outlier removal from features, the second was for feature selection, and the third was for partial-features-availability-aware ML model selection. …”
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A Robust Firearm Identification Algorithm of Forensic Ballistics Specimens by Z. L., Chuan, A. A., Jemain, C-Y, Liong, N. A. M., Ghani, L. K., Tan

“…Therefore, the aim of this study is to propose a robust algorithm for a firearm identification based on extracting a set of informative features from the segmented region of interest (ROI) using the simulated noisy center-firing pin impression images. …”
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Detection of DDoS attacks in IoT networks using machine learning algorithms by Abdulrahman Alwan, Alwan Ahmed, Shah, Asadullah, Abdulrahman Alwan, Alwan Abdullah, Laghari, Shams Ul Arfeen

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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Feature points selection for markerless hand pose estimation by Morshidi, Malik Arman, Tjahjadi, Tardi

“…This paper proposes a novel selection of hand feature points for pose estimation that improves the pose estimation. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

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A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces by A. Mostafa, Salama, Ravi, Sharran, Zebari, Dilovan Asaad, Zebari, Nechirvan Asaad, Mohammed, Mazin Abed, Nedoma, Jan, Martinek, Radek, Deveci, Muhammet, Ding, Weiping

“…A data augmentation algorithm is used for feature generation to enhance the model’s training robustness. …”
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Development Of A Robust Blind Digital Video Watermarking Algorithm Using Discrete Wavelet Transform by Al-Deen, Ahmed A. Baha'a

“…Video watermarking technology enables us to hide an imperceptible, robust, and secure data in digital or analog video. …”
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Application of BukaGini algorithm for enhanced feature interaction analysis in intrusion detection systems by Bouke, Mohamed Aly, Abdullah, Azizol, Cengiz, Korhan, Akleylek, Sedat

“…This article presents an evaluation of BukaGini, a stability-aware Gini index feature selection algorithm designed to enhance model performance in machine learning applications. …”
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TB-FusionNet: a multi-scale feature fusion algorithm with spatial and channel cross-attention for tuberculosis detection by Ding, Zeyu, Yaakob, Razali, Tieng Wei, Koh, Azman, Azreen, Mohd Rum, Siti Nurulain, Zakaria, Nor Fadhlina, Ahmad Nazri, Azree Shahril

“…The algorithm first calculates the similarity between local features at different levels to precisely select low-level detail features that are closely related to high-level semantic features, thereby generating a more hierarchical feature representation. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…Feature extraction and selection reduces the number of features. …”
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Landmark Recognition Model for Smart Tourism using Lightweight Deep Learning and Linear Discriminant Analysis by Mohd Norhisham Razali, Enurt Owens Nixon Tony, Ag Asri Ag Ibrahim, Rozita Hanapi, Zamhar Iswandono Awang Ismail

“…The landmark recognition model was evaluated by using several pretrained CNN architectures for feature extraction. Then, several feature selections and machine learning algorithms were also evaluated to produce a super lightweight and robust landmark recognition model. …”
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