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Research ArticleOpen accessIn the abstractNovel Depression Classification Framework Using Optimal Feature Integration with Hybrid Convolution (1D/3D) Based Adaptive Residual DenseNetB. Manjulatha, Suresh PabbojuThis study introduces a novel depression classification method by incorporating multimodal data to reduce this limitation and improve the accuracy of depression diagnosis. In the beginning, the multimodal data such as speech signal, Electroencephalographic (EEG), and text data is obtained from the benchmark datasets. These acquired text data are subjected to the text pre-processing phase, where the stemming, character removal, … …Journal of Computer Science, Vol. 21, Issue 3 · 25 Feb 2025 · 5,860 accessesView PDFCite
Research ArticleOpen accessIn the abstractPainting Psychotherapy Image Measurement and Reconstruction Algorithm based on Improved Hadamard MatrixMin Wan, Qiang Yang, Huajun WangPainting psychotherapy based on Internet technology has become a method of mental health testing and treatment. This method will produce a large number of digital images of painting psychotherapy. How to measure and reconstruct the image is the basis of automatic analysis and processing. This study aimed to propose a painting psychotherapy image measurement and reconstruction algorithm based on the … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 4 · 6 Nov 2020 · 6,781 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpeech Signal Analysis in Phase DomainHusne Ara Chowdhury, Mohammad Shahidur RahmanSpeech signal analysis based on the Phase Spectrum (PS) in the recent years becomes more popular to the researchers due to its attractive properties. Though some problem arises during its processing but appropriate modification gives the useful result. In this study, we proposed a new method of speech signal analysis based on its phase spectral representation. After analyzing the PS … …Journal of Computer Science, Vol. 16, Issue 8 · 10 Aug 2020 · 6,737 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Guided Anatomical Landmark and Abnormality Detection for Autonomous Endoscopy ExaminationMd Shakhawat Hossain, Munim Ahmed et al.Aabakken, L., Barkun, A. N., Cotton, P. B., Fedorov, E., Fujino, M. A., Ivanova, E., Kudo, S., Kuznetzov, K., De Lange, T., Matsuda, K., Moine, O., Rembacken, B., Rey, J., Romagnuolo, J., Rösch, T., Sawhney, M., Yao, K., & Waye, J. D. (2014). Standardized endoscopic reporting. Journal of Gastroenterology and Hepatology, 29(2), 234–240. https://doi.org/10.1111/jgh.12489 Aliyi, S., Dese, K., & Raj, … …Journal of Computer Science, Vol. 20, Issue 8 · 29 May 2024 · 6,783 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign and Implementation of Myoelectric Controlled ArmTariq M. Younes, Mohammad A. AlKhedher, Abdel-Hamid Soliman, Aiman Al AlawinIn this study a discrimination system, using a neural network for Electromyogram (EMG) externally controlled Arm is proposed. In this system, the Artificial Neural Network (ANN) is used to learn the relation between the power spectrum of EMG signal analysed by Fast Fourier Transform (FFT) and the performance desired by handicapped people. The Neural Network can discriminate 4 performances of … …Journal of Mechatronics and Robotics, Vol. 3, Issue 1 · 16 Sep 2019 · 6,281 accessesView PDFCite
Research ArticleOpen accessIn the abstractNon-Decimated Wavelet Transform and Vector Quantization for Lossy Medical Images CompressionHend A. Elsayed, Qusay E. Majeed, Mohammed M. El SherbinyThis study presents a new approach for lossy medical image compression using vector quantization. Recently, the digital image has been a reliable replacement for a hard copy of medical images, therefore, an effort has been made to ensure maintaining high-quality images to use for archiving, classification, or automated diagnostics support. Although the medical application contains all sorts of the images … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 5,403 accessesView PDFCite
Research ArticleOpen accessIn the abstractFractal Dimension for Lung Sound Classification in Multiscale SchemeAchmad Rizal, Risanuri Hidayat, Hanung Adi NugrohoLung sound is a biological signal with the information of respiratory system health. Health lung sound can be differentiated from other pathological sounds by auscultation. This difference can be objectively analyzed by a number of digital signal processing techniques. One method in analyzing the lung sound is signal complexity analysis using fractal dimension. To improve the accuracy of lung sound … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 9,279 accessesView PDFCite