Two-Sided Clifford-Valued Special Affine Fourier Transform: Properties and Associated Convolution by Shahbaz Rafiq, M. Younus Bhat

“…The primary focus of the present study is to analyse the Clifford-valued functions by introducing the notion of a two-sided Clifford-valued special affine Fourier transform in L2(Rn,Cl0,n). …”
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Certain classes of harmonic functions pertaining to special functions by G. Murugusundaramoorthy, K. Vijaya, K. Thilagavathi

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AI-Driven Innovation Using Multimodal and Personalized Adaptive Education for Students With Special Needs by Nesren Farhah, Muhammad Adnan, Ahmed Abdullah Alqarni, M. Irfan Uddin, Theyazn H. H. Aldhyani

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SEM-Net: A Social–Emotional Music Classification Model for Emotion Regulation and Music Literacy in Individuals with Special Needs by Yu-Chi Chou, Shan-Ken Chien, Pen-Chiang Chao, Yuan-Jin Lin, Chih-Yun Chen, Kuang-Kai Yeh, Yen-Chia Peng, Chen-Hao Tsao, Shih-Lun Chen, Kuo-Chen Li

“…SEM-Net employs a convolutional neural network (CNN) architecture composed of 17 meticulously structured layers to capture complex emotional and musical features effectively. …”
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Analysis of scalar fields with series convolution by Emir Baysazan, Tolga Birkandan, İsmail Eyüphan Ünver

“…In the cases where such transformations are not available, the infinite series expansions of these functions can be convoluted with the power series solution ansatz. We study such an example where the solution is based on a special function.…”
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Multi-S3P: Protein Secondary Structure Prediction With Specialized Multi-Network and Self-Attention-Based Deep Learning Model by M. M. Mohamed Mufassirin, M. A. Hakim Newton, Julia Rahman, Abdul Sattar

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A Generalization of the Fractional Stockwell Transform by Subbiah Lakshmanan, Rajakumar Roopkumar, Ahmed I. Zayed

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Graph convolution network for fraud detection in bitcoin transactions by Ahmad Asiri, K. Somasundaram

“…We have run different algorithms for predicting illicit transactions like Logistic Regression, Long Short Term Memory, Support Vector Machine, Random Forest, and a variation of Graph Neural Networks, which is called Graph Convolution Network (GCN). GCN is of special interest in our case. …”
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A convolutional autoencoder framework for ECG signal analysis by Ugo Lomoio, Patrizia Vizza, Raffaele Giancotti, Salvatore Petrolo, Sergio Flesca, Fabiola Boccuto, Pietro Hiram Guzzi, Pierangelo Veltri, Giuseppe Tradigo

“…Analysis of time varying signals may be done by using autoencoders (AEs) deep neural networks. AE specialized for signal data, named Convolutional Autoencoder (CAE), showed the best performances in the analysis of ECG signals.This paper presents a CAE-based framework for ECG signal analysis and anomaly identification. …”
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New data about library service quality and convolution prediction by Minh Tuan Nguyen, Meesad Phayung, Van Hieu Duong, Maliyaem Maleerat

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New data about library service quality and convolution prediction by Minh Tuan Nguyen, Meesad Phayung, Van Hieu Duong, Maliyaem Maleerat

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The Laguerre transform of a convolution product of vector-valued functions. by A. O. Muzychuk

“…The Laguerre transform is applied to the convolution product of functions of a real argument (over the time axis) with values in Hilbert spaces. …”
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On the Laplace Transforms of Derivatives of Special Functions with Respect to Parameters by Sergei Rogosin, Filippo Giraldi, Francesco Mainardi

“…This article is devoted to the derivation of the Laplace transforms of the derivatives with respect to parameters of certain special functions, namely, the Mittag–Leffler-type, Wright, and Le Roy-type functions. …”
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Klasifikasi Penyakit Pneumonia menggunakan Metode Convolutional Neural Network (CNN) by irfan office

“…COVID-19 pneumonia is a serious condition that requires special attention because of its contagious nature and its severe symptoms, including high fever, difficulty breathing, and lack of oxygen. …”
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AFD: Defending Convolutional Neural Networks Without Using Adversarial Samples by Nupur Thakur, Yuzhen Ding, Baoxin Li

“…In this paper, we present a novel training strategy named Adversarial-Free Defense (AFD), which introduces a minimal change to a network architecture (by modifying the first convolution layer) while employing a learning algorithm that leads to special properties of the first-layer kernels. …”
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Image-Based Iron Slag Segmentation via Graph Convolutional Networks by Wang Long, Zheng Junfeng, Yu Hong, Ding Meng, Li Jiangyun

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Crop classification with deep convolutional neural network based on crop feature by Mohamad Reza Gili, Davoud Ashourloo, Hosein Aghighi, Ali Akbar Matkan, Alireza SHakiba

“…In the next step, the functions that were developed as phenological features for crops were applied on the time series of the bands, and for each crop, a feature channel was obtained as the special feature of that crop. Then the algorithm was implemented using these feature channels in the test area and the overall accuracy was upgraded to 86% and the kappa coefficient to 0.82 compared to which indicated a significant improvement in the results compared to the previous case.Conclusion:The deep convolutional neural network is very sensitive to the type of input channels for detecting agricultural crops and selecting the channels with suitable tempo-spectral characteristics for different types of crops, has a great impact on the accuracy of network training and can reduce the loss of training network and increase its efficiency in the classification of various crops.…”
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On-Chip Photonic Convolutional Processing Lights Up Fourier Neural Operator by Zilong Tao, Hao Ouyang, Qiuquan Yan, Shiyin Du, Hao Hao, Jun Zhang, Jie You

“…However, the absence of specialized photonic hardware has limited the acceleration of FNO inference. …”
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SAGCN: Self-Attention Graph Convolutional Network for Human Pose Embedding by Zhongxiong Xu, Jiajun Hong, Yicong Yu, Chengzhu Lin, Linfei Yu, Meixian Xu

“…While traditional convolutional neural networks (CNNs) have advanced pose feature extraction, they struggle to model structural relationships and long-range dependencies between keypoints, and are less robust to occlusions. …”
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Convolutional sparse coding network for sparse seismic time-frequency representation by Qiansheng Wei, Zishuai Li, Haonan Feng, Yueying Jiang, Yang Yang, Zhiguo Wang

“…In this design, we replace the conventional convolutional layers of the UNet with learnable iterative shrinkage thresholding algorithm (LISTA) blocks, a specialized form of CSC. …”
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