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Preprocessing Techniques for End-To-End Trainable RNN-Based Conversational System
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…This conclusion was achieved after preprocessing a number of data values from these data sets.…”
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Unsupervised outlier detection in multidimensional data
Published 2022“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. …”
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…These data contained parameters regarding air (Ornge) and land medical transport (3 services), which were preprocessed and cleaned. …”
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A Multi-Faceted Approach to Trending Topic Attack Detection Using Semantic Similarity and Large-Scale Datasets
Published 2025“…A novel data augmentation technique further enriched the quality and diversity of these datasets. …”
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Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure
Published 2020“…This work presents a procedure for improving the accuracy of modeled solar irradiance series through site-adaptation with coincident ground-based measurements relying on the use of a regression preprocessing followed by an empirical quantile mapping (eQM) correction. …”
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Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations
Published 1992“…Three optimization methods derived from natural sciences are considered for allocating data to multicomputer nodes. These are simulated annealing, genetic algorithms and neural networks. …”
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A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…Moreover, the DBRF classification model is deployed to categorize the normal and attacking data flows using optimized features. Here, the proposed DRF-DBRF security model's performance is validated and tested using five different and popular IoT benchmarking datasets. …”
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Developing Privacy Frameworks for Motion Sensor Data in Next-Generation Wearable Devices
Published 2025Get full text
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Deep learning-based marine big data fusion for ocean environment monitoring: Towards shape optimization and salient objects detection
Published 2023“…Moreover, we used preprocessing techniques before the classification task for underwater image enhancement, segmentation, noise and fog removal, restoration, and color constancy.…”
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Sensor-based Continuous Arabic Sign Language Recognition
Published 2014Get full text
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Driver stress level detection using HRV analysis
Published 2017“…In our study, the ECG signal of the driver is extracted and preprocessed in order to perform the HRV analysis. This analysis is accomplished using one of the domain analysis approach such as time, frequency, time-frequency or non-linear methods including Wavelet and STFT. …”
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An approach to offline Arabic character recognition using neural networks
Published 2003“…Character recognition system can contribute tremendously towards the advancement of automation process and can be useful in many other applications such as Data Entry, Check Verification etc. …”
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Arabic Dialect Speech-Text Recognition Using Deep Learning
Published 2024“…The research begins with a comprehensive preprocessing process, which involves loading audio data, extracting features using Mel-Frequency Cepstral Coefficients (MFCCs), and encoding labels. …”
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Breast Density Estimation in Mammograms Using Unsupervised Image Segmentation
Published 2023Get full text
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Enhancement of SAR Speckle Denoising Using the Improved Iterative Filter
Published 2020“…Simulated, airborne (ESAR, Oberpfaffenhofen Germany) and spaceborne (Sentinel 1, Palm Jumeirah Dubai UAE) SAR data were used to assess the filtering performances of the studied filters.…”
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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…Based on the existence of cyberbullying, the data was then preprocessed and classified. In this work, two cases of classification were adapted. …”
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