Search Results - (( motion estimation from algorithm ) OR ( _ identification clustering algorithm ))

Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

“…Block-matching algorithm is the most common technique applied in block-based motion estimation technique. …”
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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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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

“…It has been observed that the real world video sequences exhibit a wide range of motion content, from uniform to random, therefore if the motion characteristics of video sequences are taken into account before hand, it is possible to develop a robust motion estimation algorithm that is suitable for all kinds of video sequences. …”
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New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique by Hamid, Nurul 'Atiqah

“…Motion Estimation or ME is deemed as one of the effective and popular techniques in video compression. …”
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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

“…Moreover, we investigate the behavior of our algorithm under challenging conditions including the subject's motions and illumination variation, which shows that our algorithm can reduce the influences of illumination interference and rigid motions significantly. …”
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REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION by RUZALI, RUZALI

“…The optical flow constraint equation of Horn-Schunck (OFCE-HS) is an algorithm used to compute motion estimation from the apparent motion of image sequences. …”
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi by Hosseiny Fatemi, Mohammad Reza

“…This thesis is concerned with algorithm optimization and efficient low cost architecture design for integer motion estimation (IME) and sub-pixel motion estimation (SME) of H.264/AVC. …”
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BLOCK MOTION ESTIMATION USING DIRECTIONAL ADAPTIVE SEARCH WINDOW by Fadly Chew, NorFarhana

“…The algorithm determines the amount of motion in each block and classifies them as low, medium and high motion. …”
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The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes by Abd Halim, Zakiah, Jamaludin, Nordin, Putra, Azma

“…The AR algorithm characterizes the shape of the stress wave signals by AR coefficients and clustered using ‘centroid’ linkages. …”
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SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

“…This study presents the identification of slow drift motions of floating structures from model test data. …”
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
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Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

“…The proposed fall risk clustering algorithm grouped the subjects according to features. …”
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Extract Motion from Picture Sequence by MOHD SHAFIQ AHMAD DAHALAN, MOHD SHAFIQ

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Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering by Umelo, Nnamdi Henry, Noordin, Nor Kamariah, A. Rasid, Mohd Fadlee, Tan, Kim Geok, Hashim, Fazirulhisyam

“…In the initialization stage, the reader uses improved K-means clustering running concurrently with a tag counter algorithm to cluster tags into K groups using tags RN16 while the counter returns an accurate tag number estimate. …”
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Application of fuzzy clustering analysis to compound datasets for drug lead identification by Sinarwati, Mohamad Suhaili, Mohamad Nazim, Jambli, Abdul Rahman, Mat

“…However, there are little study on overlapping method such as fuzzy cmean (FCM) and fuzzy c-varieties (FCV) clustering algorithms. Therefore, these two clustering algorithms are applied and their performance is compared based on the effectiveness of the clustering results in terms of separation between actives and inactives (Pa) into different clusters and mean intercluster molecular dissimilarity (MIMDS). …”
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MOTION ESTIMATION IN BRAIN TOPOGRAPHIC MAPS by GOPALAKRISHNAN, GOWRI

“…Currently, no proper motion estimation technology is available for this purpose. …”
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Tracking of EEG Activity Using Motion Estimation to Understand Brain Wiring by Nisar, Humaira, Malik, Aamir Saeed, Ullah, Rafi, Shim, Seongo, Bawakid, Abdullah, Khan, Muhammad Burhan, Subhani, Rauf

“…Using motion estimation it is possible to track the path from the starting point of activation to the final point of activation. …”
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MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION by SAINI, SANJA Y

“…However. extracting the articulated human body motion from multi-view synchronized video stream is a dit1icult task due to the underlying multimodal and high dimensional estimation problem. …”
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Document clustering for knowledge discovery using nature-inspired algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…As the internet is overload with information, various knowledge based systems are now equipped with data analytics features that facilitate knowledge discovery.This includes the utilization of optimization algorithms that mimics the behavior of insects or animals.This paper presents an experiment on document clustering utilizing the Gravitation Firefly algorithm (GFA).The advantage of GFA is that clustering can be performed without a pre-defined value of k clusters.GFA determines the center of clusters by identifying documents with high force.Upon identification of the centers, clusters are created based on cosine similarity measurement.Experimental results demonstrated that GFA utilizing a random positioning of documents outperforms existing clustering algorithm such as Particles Swarm Optimization (PSO) and K-means.…”
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