Search Results - signal data processing and classification

Cross-Dataset Head-Related Transfer Function Harmonization Based on Perceptually Relevant Loss Function by Jiale Zhao, Dingding Yao, Junfeng Li

“…The recent Listener Acoustic Personalization Challenge 2024 (European Signal Processing Conference) dealt with this issue, with the task of harmonizing different datasets to achieve lower classification accuracy while meeting thresholds over various localization metrics. …”
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Federated Learning With Automated Dual-Level Hyperparameter Tuning by Rakib Ul Haque, Panagiotis Markopoulos

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Rehabilitation and Motion Symmetry Analysis With a TACX Smart Cycling Trainer Using Computational Intelligence by Hana Charvatova, Daniel Martynek, Alexandra Molcanova, Ales Prochazka

“…Signal processing is conducted using advanced methods that include computational intelligence, digital signal processing, and artificial intelligence tools for data classification. …”
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Uncertainty-Aware Deep Learning for Robust and Interpretable MI EEG Using Channel Dropout and LayerCAM Integration by Óscar Wladimir Gómez-Morales, Sofia Escalante-Escobar, Diego Fabian Collazos-Huertas, Andrés Marino Álvarez-Meza, German Castellanos-Dominguez

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Rolling Bearing Fault Diagnosis Method Based on Fusion of CNN and CSSVM by LI Yunfeng, LAN Xiaosheng, SHEN Hongchang, XU Tongle

“…Aiming at the problems of low classification accuracy and weak model generalization ability of traditional fault diagnosis classification methods in the fault diagnosis of rolling bearings in rotating machinery, an intelligent fault diagnosis model based on signal processing technology combined with deep learning algorithm was proposed. …”
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IARA: An Underwater Acoustic Database by Fabio Oliveira Baptista Da Silva, Julio De Castro Vargas Fernandes, William Soares Filho, Joao Baptista De Oliveira E Souza Filho, Angela Spengler, Natanael Nunes De Moura

“…The study also emphasizes the importance of proper data selection, including the use of exclusion regions to enhance signal confidence. …”
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FPGA implementation of normalized correlation function by Krzysztof Mroczek

“…Correlation analysis is a frequently used tool in signal detection and classification tasks. This paper presents the design and FPGA implementations of a hardware module for calculating the Pearson correlation coefficient. …”
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Convolutional neural network for IT lung diagnostics by U. A. Vishniakou, T. He

“…A block diagram of voice processing from the source signal to the extraction of an audio file is presented, as an example, the extraction of MFCC and FBank functions is given. …”
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THE METHOD OF JITTER DETERMINING IN THE TELECOMMUNICATION NETWORK OF A COMPUTER SYSTEM ON A SPECIAL SOFTWARE PLATFORM by Mykhailo Mozhaiev, Nina Kuchuk, Maksym Usatenko

“…Also, when constructing, modifying and operating telecommunication networks, there is a rather common problem with no digital signal processing, network synchronization and stability. …”
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Identifikasi Emosi Manusia Berdasarkan Ucapan Menggunakan Metode Ekstraksi Ciri LPC dan Metode Euclidean Distance by Siti Helmiyah, Imam Riadi, Rusydi Umar, Abdullah Hanif, Anton Yudhana, Abdul Fadlil

“…Information that can be captured from speech can be in the form of messages to interlocutor, the speaker, the language, even the speaker's emotions themselves without the speaker realizing it. Speech Processing is a branch of digital signal processing aimed at the realization of natural interactions between humans and machines. …”
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A Multimodal Multi-Stage Deep Learning Model for the Diagnosis of Alzheimer’s Disease Using EEG Measurements by Tuan Vo, Ali K. Ibrahim, Hanqi Zhuang

“…<b>Methods:</b> This study introduces a novel methodology employing three distinct stages for data-driven AD diagnosis: signal pre-processing, frame-level classification, and subject-level classification. …”
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Using Generative Adversarial Networks to Translate Microresistivity Image Logs of Carbonates Into Synthetic Core Images With Accurate Dunham Textures by Saira Baharuddin, Cédric M. John

“…We trained a total of 10 models, testing various combinations of FMS data input formats, image processing methods, GAN architecture, and training hyperparameters. …”
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Red-KPLS Feature Reduction with 1D-ResNet50: Deep Learning Approach for Multiclass Alzheimer’s Staging by Syrine Neffati, Ameni Filali, Kawther Mekki, Kais Bouzrara

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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

“…ML enables large-scale data processing, offering novel opportunities for diagnosing and treating mental disorders. …”
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Formation of the pediatric electroretinogram database parameters for the development of doctor’s decisionmaking algorithm by A. E. Zhdanov, A. Yu. Dolganov, V. N. Kazaykin, V. I. Borisov, V. O. Ponomarev, L. G. Dorosinsky, A. V. Lizunov, E. Luchian, X. Bao

“…The classification of electroretinogram signals depends on the quality of labeled biomedical information or databases, in addition to this, the accuracy of the classification results obtained depends not only on computer technology, but also on the quality of the input data. …”
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Smart and Secure Healthcare with Digital Twins: A Deep Dive into Blockchain, Federated Learning, and Future Innovations by Ezz El-Din Hemdan, Amged Sayed

“…A case study on federated learning for electroencephalogram (EEG) signal classification is presented, demonstrating its potential as a diagnostic tool for brain activity analysis and neurological disorder detection. …”
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Key Vital Signs Monitor Based on MIMO Radar by Michael Gottinger, Nicola Notari, Samuel Dutler, Samuel Kranz, Robin Vetsch, Tindaro Pittorino, Christoph Würsch, Guido Piai

“…The first step is enabled by processing radar data with a forked convolutional neural network, which is trained with reference data captured by a time-of-flight depth camera. …”
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Multifocus Images Fusion Based On Homogenity and Edges Measures by Baghdad Science Journal

“…Image fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. …”
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Enhancing FTIR Spectral Feature Construction for Aero-Engine Hot Jet Remote Sensing via Integrated Peak Refinement and Higher-Order Statistical Fusion by Zhenping Kang, Yurong Liao, Xinyan Yang, Zhaoming Li

“…Regarding the issue of constructing Fourier transform infrared (FTIR) spectral characteristics of hot jet of aero-engines, this paper presented a construction algorithm for the FTIR spectral characteristics of an aero-engine hot jet, which integrated staged refined processing and statistical feature fusion. First, a remote-sensing Fourier transform infrared spectrometer was employed to collect data on the hot jets of two distinct types of aero-engines, thereby establishing a measured spectral dataset. …”
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AADNet: An End-to-End Deep Learning Model for Auditory Attention Decoding by Nhan Duc Thanh Nguyen, Huy Phan, Simon Geirnaert, Kaare Mikkelsen, Preben Kidmose

“…Auditory attention decoding (AAD) is the process of identifying the attended speech in a multi-talker environment using brain signals, typically recorded through electroencephalography (EEG). …”
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