Search Results - (( process motion learning algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893)
Published 2017“…The significant contribution for this study is that the learning rule (e.g. STDP algorithm) has learning capability in memory recall. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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Conference or Workshop Item -
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…Motion target detection and tracking are among the most important computer vision areas that use advanced image processing techniques. …”
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Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation
Published 2000“…Then, various optimized algorithms for the two core processes in the compression, DCT and motion estimation, were reviewed and analyzed. …”
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Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood
Published 2015“…The results show that the imitation learning algorithm is able to incrementally learn and associate the observed motion patterns based on the segmentation of motion primitives.…”
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Design and performance analysis of artificial neural network for hand motion detection from EMG signals
Published 2013“…The neural network is of backpropagation type, trained by Levenberg-Marquardt training algorithm. Before the classification process, the EMG signals have been pre-processed for extracting some features from them. …”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments
Published 2022“…On the other hand, learning-based methods automatically learn the features required through motion mapping. …”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments
Published 2022“…On the other hand, learning-based methods automatically learn the features required through motion mapping. …”
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Identification and control of a small-scale helicopter
Published 2010“…This identification process is based on the well-known gradient descent learning algorithm. …”
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A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem
Published 2018“…In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Abnormal event detection in video surveillance / Lim Mei Kuan
Published 2014“…Therefore, by considering tracking as an optimisation problem, the proposed SwATrack algorithm searches for the optimal distribution of motion model without making prior assumptions, or prior learning of the motion model. …”
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