Search Results - signal data processing and classification

A comparative analysis of emotion recognition from EEG signals using temporal features and hyperparameter-tuned machine learning techniques by Rabita Hasan, Sheikh Md. Rabiul Islam

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A comparative study to examine principal component analysis and kernel principal component analysis-based weighting layer for convolutional neural networks by Amir Mehrabinezhad, Mohammad Teshnehlab, Arash Sharifi

“…In the recent decay, the focus on processing signal data processing such as time series, images, and videos increased. …”
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Quality-Aware PPG-Based Blood Pressure Classification for Energy-Efficient Trustworthy BP Monitoring Devices With Reduced False Alarms by Yalagala Sivanjaneyulu, M. Sabarimalai Manikandan, Srinivas Boppu, Linga Reddy Cenkeramaddi

“…For the case of processing a 60s noisy PPG signal, the QA-BP method had an energy saving of 41.3% with display mode and an energy saving of 95.3% with the data transfer mode as compared to the BP classification method without the SQA approach. …”
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Sensitivity Study of Feature Vectors Formed on the Basis of Multiple Scale Transformations of Processed Images by D. V. Vasilieva

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A Systematic Literature Review of Machine Learning-Based Personality Trait Detection Using Electroencephalographic Data by Celina Rieck, Pascal Penava, Ricardo Buettner

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Neural network approaches, including use of topological data analysis, enhance classification of human induced pluripotent stem cell colonies by treatment condition. by Alexander Ruys de Perez, Paul E Anderson, Elena S Dimitrova, Melissa L Kemp

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Intelligent Hybrid SHM-NDT Approach for Structural Assessment of Metal Components by Romaine Byfield, Ahmed Shabaka, Milton Molina Vargas, Ibrahim Tansel

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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

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Development and evaluation of machine learning models for premixed flame classification in different hydrogen-natural gas proportions using images and audio by Pedro Narvaez, Alejandro Lopez, Jousef E. Karam, Alejandro Restrepo, Andrés A. Amell

“…The feature extraction process employed convolutional neural networks (CNNs) for both data types, with a segmentation stage applied to the audio signals. …”
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A pipeline with pre-processing options to detect behaviour from accelerometer data using Machine Learning tested on dairy goats by Mauny, Sarah, Kwon, Joon, Friggens, Nicolas C., Duvaux-Ponter, Christine, Taghipoor, Masoomeh

“…This paper aims to present the use of a pipeline called ACT4Behav (Accelerometer-based Classification Tool for identifying Behaviours) involving a supervised classification algorithm for automatically characterising specific animal behaviours using accelerometer data, and to explore the best pre-processing steps for each behaviour. …”
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Robust neural network filtering in the tasks of building intelligent interfaces by A. V. Vasiliev, A. O. Melnikov, S. A. Lesko

“…The possibility of using artificial neural networks to identify and suppress individual human characteristics in biological signals is demonstrated. When training the network, the main emphasis was placed on individual features by testing the network on data received from subjects not involved in the learning process. …”
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Enhanced Pilot Attention Monitoring: A Time-Frequency EEG Analysis Using CNN–LSTM Networks for Aviation Safety by Quynh Anh Nguyen, Nam Anh Dao, Long Nguyen

“…Finally, our dual-architecture CNN–LSTM model processes spatial patterns via CNNs while capturing temporal degradation signals via LSTMs, enabling robust classification in noisy operational environments. …”
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An Attention-Enhanced 3D-CNN Framework for Spectrogram-Based EEG Analysis in Epilepsy Detection by Ziaullah Khan, Aakanksha Dayal, Hee-Cheol Kim

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Advancements in epilepsy classification: Current trends and future directions by Rajani Rai B, Karunakara Rai B, Mamatha A S, Kavitha Sooda

“…The paper synthesizes cutting-edge techniques with the focus on the application of hybrid models that combine traditional signal processing techniques with machine learning algorithms. …”
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ANALYSIS OF RADIO SIGNAL PARAMETERS FOR EMISSION SOURCE IDENTIFICATION by D. V. Arkhipenkov

“…Autocorrelation is used to determine signal parameters such as the transmission duration, data block duration. …”
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Mifu-ER: Modality Quality Index-Based Incremental Fusion for Emotion Recognition by Sun-Hee Kim

“…Recently, there has been a growing trend in emotion recognition studies to use multimodal data that fuses more than two physiological signals to improve emotion recognition performance based on this physiological information. …”
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Classification of α wave motor imagery based on SVM and PCA by Cai Jing, Liu Guangda, Wang Yaoyao, Gong Xiaoyu

“…According to the selected data, the accuracy of the results is higher, and the accuracy of signal classification is improved from 90.1% to 94.0%.…”
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Efficient Real-Time Isotope Identification on SoC FPGA by Katherine Guerrero-Morejón, José María Hinojo-Montero, Jorge Jiménez-Sánchez, Cristian Rocha-Jácome, Ramón González-Carvajal, Fernando Muñoz-Chavero

“…A key feature of the design is its ability to perform real-time classification without storing ADC samples, directly processing nuclear pulse data as it is acquired. …”
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FEATURE SELECTION AND CLASSIFICATION OF LEUKEMIC CELLS USING IOT AND MACHINE LEARNING by K. R.Vineetha, Kovvuri N. Bhargavi, G. L. Narasamba Vanguri, Jenifer Mahilraj, V. Kannan

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Semi-Supervised Learned Autoencoder for Classification of Events in Distributed Fibre Acoustic Sensors by Artem Kozmin, Oleg Kalashev, Alexey Chernenko, Alexey Redyuk

“…Additionally, advanced signal processing algorithms are necessary for accurately determining the location and nature of detected events. …”
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