Search Results - (( motion extraction method algorithm ) OR ( level classification search algorithm ))

Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

“…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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Fast adaptive motion estimation search algorithm for H.264 encoder by Patwary, Md Anwarul Kaium

“…Motion estimation is a technique of video compression and video processing applications; it extracts motion information from the video sequence. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The result shows the area under the ROC curve (AUC) of 0.804 with p < 0.0001 at 95% confidence level. Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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A new search and extraction technique for motion capture data by Mohamad, Rafidei

“…Results from the experiments show that matching motion files were successfully extracted from the motion capture library using the new algorithm based on different human body segments.…”
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Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter by Nooralishahi, Parham, Loo, Chu Kiong, Shiung, Liew Wei

“…The method employs the RADICAL technique to extract independent subcomponents. …”
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Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

“…SIPIDRIP generated shorter rules among other methods in most dataset. The proposed search strategy indicated that the best performance can be achieved at the lower level or shorter path of the tree search. …”
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Fingerprint classification : a BI-resolution approach to singular point extraction by Leong, Chung Ern

“…The algorithm will only search for singular points in the finer level in a particular region if and only if there is a hit. …”
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Motion detection using Horn-Schunck optical flow by Wan Nur Azhani, W. Samsudin, Kamarul Hawari, Ghazali

“…This system is design to detect motion in a crowd using one of the optical flow algorithms, Horn-Schunck method. …”
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Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…This decreases the detection efficiency and degrades the target tracking output. Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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A method for motion tracking of ventricular endocardial surface by O. K. Rahmat, Rahmita Wirza, Dawood, Faten Abed Ali, Dimon, Mohd Zamrin, Kadiman, Suhaini, Abdullah, Lili Nurliyana

“…The present invention relates to a method for automatic motion tracking of ventricular endocardial surface in three dimensional (3D) echocardiography, characterized by the steps of extracting a plurality of ventricular endocardial contours over a complete cardiac cycle; identifying a plurality of landmarks on each ventricular endocardial contour; measuring displacement vector flow (DVF) for each landmark by comparing a pair of consecutive ventricular endocardial contours; measuring velocity vector flow (VVF) for each landmark from end-diastolic (ED) to end-systolic (ES) and vice versa; identifying at least four landmarks from the plurality of landmarks on each ventricular endocardial contour to represent anatomical landmarks of left lateral surface, right lateral surface, inferior wall and anterior wall by using geometrical distance calculation (GDC) algorithm; analysing ventricular endocardial motion direction using a fuzzy logic analyzer (FLA) for the four landmarks identified; updating values of the displacement vector flow (DVF) and velocity vector flow (VVF) based on the ventricular endocardial motion direction; and generating graphical curves of time versus values of the displacement vector flow (DVF) and velocity vector flow (VVF) for the four landmarks identified.…”
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Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition by Al-Qammaz, Abdullah Yousef, Ahmad, Farzana Kabir, Yusof, Yuhanis

“…Whereby, the max accuracy obtained is 66.66% and 70.83%, the mean accuracy obtained is 55.51±7.17 and 60.97±8.38 for 3-level of valence emotions and 3-level of arousal emotions classification respectively.…”
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Design and performance analysis of artificial neural network for hand motion detection from EMG signals by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

“…The conventional and most effective time and timefrequency based features are extracted and normalized. The neural network has been trained with the normalized feature set with supervised learning method. …”
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Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm by Taman, Ishak, Md Rosid, Nur Atika, Karis, Mohd Safirin, Hasim, Saipol Hadi, Zainal Abidin, Amar Faiz, Nordin, Nur Anis, Omar, Norhaizat, Jaafar, Hazriq Izzuan, Ab Ghani, Zailani, Hassan, Jefery

“…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network by Nazriyah, Haji Che Zan @ Che Zain

“…Statistical based features namely minimum, maximum, arithmetic average and standard deviation were extracted from each image channels within detected ROI to represent pineapple skin color's tendency and dispersion. Next, classification index to determine the pineapple maturity level has been applied which are linear classification using thresholding value and artificial neural network adopting pattern recognition method. …”
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Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

“…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

“…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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Efficient classifying and indexing for large iris database based on enhanced clustering method by Khalaf, Emad Taha, Mohammed, Muamer N., Kohbalan, Moorthy, Khalaf, Ahmad Taha

“…From the experimental results, the proposed method was indeed more effective for clustering and classification and outperformed the traditional k-mean algorithm. …”
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Multi-level of feature extraction and classification for X-Ray medical image by Abdulrazaq, M, Alshaikhli, Imad Fakhri Taha, Mohd Noah, Shahrul Azman, Fadhil,, Moayad Al Athami

“…Therefore, effective techniques for medical image retrieval and classification are required to provide accurate search through substantial amount of images in a timely manner. …”
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Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

“…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…However, there is no single study focusing on pallet-level classification, in particular on distance measurement of pallet height. …”
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