Search Results - (( pattern detection clustering algorithm ) OR ( java application optimization algorithm ))
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Image clustering comparison of two color segmentation techniques
Published 2010“…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images
Published 2024Conference Paper -
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RFID-enabled supply chain detection using clustering algorithms
Published 2015“…We will apply various clustering algorithms to analyzed and determine every attribute in the dataset structure pattern. …”
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Classification and detection of intelligent house resident activities using multiagent
Published 2013“…Result shows that, the algorithm can successfully identify 135 unique tasks of different lengths.This algorithm is surely being an alternate way of pattern recognition in intelligent home.…”
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Detection of tube defect using the autoregressive algorithm
Published 2015“…This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. …”
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Evaluation of intonation features on emphasized Malay words / Syazwani Nasaruddin
Published 2017“…The pattern of the features such as intensity and pitch are observed and clustered to find out how many patterns can be identified from all the words. …”
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7
Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection
Published 2015“…The signals were then clustered using the feature extraction algorithms. …”
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana
Published 2018“…Anomaly-based Intrusion Detection System (IDS) uses known baseline to detect patterns which have deviated from normal behaviour. …”
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Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…Clustering is one of the promising techniques used in Anomaly Intrusion Detection (AID), especially when dealing with unknown patterns. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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11
Performance evaluation of real-time multiprocessor scheduling algorithms
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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Image Segmentation Using an Adaptive Clustering Technique for the Detection of Acute Leukemia Blood Cells Images
Published 2024Proceedings Paper -
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Application of kohonen neural network and rough approximation for overlapping clusters optimization
Published 2008“…Experiments show that the proposed two-level algorithm is more accurate and generates fewer errors as compared with crisp clustering operations.…”
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Route Optimization System
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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A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications
Published 2022“…Without human input, these algorithms discover patterns or groupings in the data. …”
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Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network
Published 2019“…In the proposed work, the focused problem is how to reduce the communication energy consumption and to avoid the routing hole problem by optimized routing algorithms. First, a routing hole detection algorithm is proposed prior to designing the routing protocol which decreases about 30 percent energy consumption rate, detection time and detection overhead. …”
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18
Identifying multiple outliers in linear functional relationship model using a robust clustering method
Published 2023“…Outliers are some observation points outside the usual pattern of the other observations. It is essential to detect outliers as anomalous observations can affect the inference made in the analysis. …”
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Low area Programmable Memory Built-In Self-Test (PMBIST) for small embedded ram cores / Nur Qamarina Mohd Noor
Published 2013“…The first experiment is performed by clustering test patterns of RAMs under test. The second experiment deeply encodes the clusters of test patterns to improve the cluster technique to allow multiple test data types. …”
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