Search Results - (( motion estimation based algorithm ) OR ( defect classification techniques algorithms ))
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1
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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2
An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images
Published 2012“…The improved PCB defect classification algorithm has been applied to real PCB images to successfully classify all of the defects. …”
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3
Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The classification algorithm is a popular machine learning approach for software defect prediction. …”
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An Adaptive Motion Estimation Algorithm for Irregular Motion of Objects
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ADAPTIVE MOTION ESTIMATION ALGORITHM FOR CROWDED SCENES
Published 2015“…Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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An adaptive block-based matching algorithm for crowd motion sequences
Published 2018“…For crowd analytics and surveillance systems, motion estimation is an essential first step. Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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An adaptive block-based matching algorithm for crowd motion sequences
Published 2018“…For crowd analytics and surveillance systems, motion estimation is an essential first step. Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…Motion estimation is a technique to reduce high information redundancy which exists between successive frames in a video sequences. …”
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9
Neural network paradigm for classification of defects on PCB
Published 2003“…A defective PCB image is used to ensure the function of the proposed technique.…”
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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification
Published 2012“…In video coding, research is focused on the development of fast motion estimation (ME) algorithms while keeping the coding distortion as small as possible. …”
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Classification Analysis Of High Frequency Stress Wave For Autonomous Detection Of Defect In Steel Tubes
Published 2014“…Interpretation of propagated high frequency stress wave signals in steel tubes is noteworthy for defect identification.This paper demonstrated a successful new approach for autonomous defect detection in steel tubes using classification analysis of high frequency stress waves.Classification analysis using Principal Component Analysis (PCA) algorithm involved feature extraction to reduce the dimensionality of the complex stress waves propagation path.Two defective tubes containing a slot defect of different orientation and a reference tube are inspected using Vibration Impact Acoustic Emission (VIAE) technique.The tubes are externally excited using impact hammer.The variation of stress wave transmission path are captured by high frequency Acoustic Emission sensor.The propagated stress waves in the steel tubes are classified using PCA algorithm.Classification results are graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of the stress wave signals.The inspection of steel tubes showed good recognition of defect in circumferential and longitudinal orientation.This approach successfully classified stress wave signals from VIAE testing and provide fast and accurate defect identification of defective steel tubes from non-defective tubes. …”
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12
Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. However, limitations such as robustness and difficulty in setting up the parameters required for image processing algorithm encourages the investigation in using Deep learning classification in detecting the wafer defects. …”
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15
An adaptive motion estimation algorithm for irregular motion of objects
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16
Automated mold defects classification in paintings: a comparison of machine learning and rule-based techniques.
Published 2025“…Subsequently, these regions are classified as mold defects using either morphological filtering or machine learning models such as Classification and Regression Trees (CART) and Linear Discriminant Analysis (LDA). …”
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Design and Development of Artificial Intelligence (Al)-Based Desicion Support System For Manufacturing Applications
Published 2016“…To perform classification of the welding defects, an artificial intelligence (AI) technique, i.e., the Fuzzy ARTMAP (FAM) neural network, is applied. …”
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Monograph -
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Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules
Published 2023“…However, high similarity of characteristics among the shapes and textures has been a major challenge in defect classification process. The objective of this research was to develop and analyse feature extraction used for classification techniques for defect detection of solar photovoltaic modules surfaces. …”
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Fast directional search algorithm for fractional pixel motion estimation for H.264 AVC
Published 2013“…Fractional pixel motion estimation (ME) is required to achieve more accurate motion vectors and higher compression efficiency. …”
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Cross-project software defect prediction
Published 2022“…In this work, five research questions covering the classification algorithms, dataset, independent variables, performance evaluation metrics used in CPDP studies, and as well as the performance of individual machine learning classification algorithms in predicting software defects across different software projects were addressed accordingly. …”
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