Fluorescence Spectroscopy and a Convolutional Neural Network for High-Accuracy Japanese Green Tea Origin Identification by Rikuto Akiyama, Kana Suzuki, Yvan Llave, Takashi Matsumoto

“…This study aims to develop a system combining fluorescence spectroscopy and machine learning through a convolutional neural network (CNN) to identify the origins of various Japanese green teas (Sayama tea, Kakegawa tea, Yame tea, and Chiran tea). …”
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A rapid fingerprint positioning method based on deep convolutional neural network for MIMO-OFDM systems by Chenlin He, Xiaojun Wang, Jiyu Jiao, Yuhua Huang, Chengpei Han, Yizhuo Zhang, Jianping Zhu

“…In this paper, we propose a fingerprint positioning method based on a deep convolutional neural network (DCNN) using a classification approach in a single-base station scenario for massive multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. …”
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Classification of Short-Segment Pediatric Heart Sounds Based on a Transformer-Based Convolutional Neural Network by Md Hassanuzzaman, Samit Kumar Ghosh, Mohammad Nurul Akhtar Hasan, Mohammad Abdullah Al Mamun, Khawza I. Ahmed, Raqibul Mostafa, Ahsan H. Khandoker

“…Mel-frequency cepstral coefficients (MFCCs) are extracted as features and fed into a transformer-based residual one-dimensional convolutional neural network (1D-CNN) for classification. …”
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Robust Registration of Multimodal Remote Sensing Images Using Self-Similar Adjacent Self-Convolutional Feature by Tian Gao, Chaozhen Lan, Liang Lv, Qunshan Shi, Wenjun Huang, Yiqiao Wang, Zhizhen Mu

“…Due to significant nonlinear radiometric differences (NRD) and severe geometric distortions (e.g., translation, scale, and rotation) among multimodal images (e.g., optical, infrared, SAR), image registration remains a challenging problem. …”
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Cross-User Electromyography Pattern Recognition Based on a Novel Spatial-Temporal Graph Convolutional Network by Mengjuan Xu, Xiang Chen, Yuwen Ruan, Xu Zhang

“…Given that high-density surface EMG (HD-sEMG) signal contains rich temporal and spatial information, the multi-view spatial-temporal graph convolutional network (MSTGCN)is adopted as the basic classifier, and a feature extraction convolutional neural network (CNN) module is designed and integrated into MSTGCN to generate a new model called CNN-MSTGCN. …”
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Numerical Estimation of Bending in Holographic Volume Gratings by Means of RCWA and Deep Learning by Jaume Colomina-Martínez, Juan Carlos Bravo, Joan Josep Sirvent-Verdú, Adrián Moya-Aliaga, Jorge Francés, Cristian Neipp, Augusto Beléndez

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Convolution Results and Fekete–Szegö Inequalities for Certain Classes of Symmetric q-Starlike and Symmetric q-Convex Functions by Tamer M. Seoudy

“…In this paper, by using the concept of the symmetric q-difference operator, we introduce certain classes of symmetric q-starlike and symmetric q-convex functions. …”
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A Seq-to-Seq Temporal Convolutional Network for Volleyball Jump Monitoring Using a Waist-Mounted IMU by Meng Shang, Camilla de Bleecker, Jos Vanrenterghem, Roel de Ridder, Sabine Verschueren, Carolina Varon, Walter de Raedt, Bart Vanrumste

“…A Multi-Layer Temporal Convolutional Network (MS-TCN) was applied for sequence-to-sequence (seq-to-seq) classification without using the sliding window technique. …”
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Characteristics Analysis of Mental Health Data of College Students Based on Convolutional Neural Network and TOPSIS Evaluation Model by Lanfeng Zhou

“…This paper develops a feature analysis method of the mental health data of students in different colleges and regions and of different ages based on a convolutional neural network and TOPSIS evaluation model and studies the college students’ mental health analysis model based on convolutional neural network. …”
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Robust Low-Snapshot DOA Estimation for Sparse Arrays via a Hybrid Convolutional Graph Neural Network by Hongliang Zhu, Hongxi Zhao, Chunshan Bao, Yiran Shi, Wenchao He

“…We propose a hybrid Convolutional Graph Neural Network (C-GNN) for direction-of-arrival (DOA) estimation in sparse sensor arrays under low-snapshot conditions. …”
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Cross-species AI: shifting a convolutional neural network from pigs to lambs to detect pneumonia at slaughter by Anastasia Romano, Antonio De Camillis, Domenico Sciota, Simona Baghini, Andrea Di Provvido, Alfonso Rosamilia, Andrea Capobianco Dondona, Nicola Bernabò, Francesca Vaccarelli, Attilio Corradi, Giuseppe Marruchella

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Using convolutional neural networks to count parrot nest‐entrances on photographs from the largest known colony of Psittaciformes by Gabriel L. Zanellato, Gabriel A. Pagnossin, Mauricio Failla, Juan F. Masello

“…Here, we took advantage of convolutional neural networks (CNN) to count the total number of nest‐entrances in 222 photographs covering the largest known Psittaciformes (Aves) colony in the world. …”
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MDGCN: Multiple Graph Convolutional Network Based on the Differential Calculation for Passenger Flow Forecasting in Urban Rail Transit by Chenxi Wang, Huizhen Zhang, Shuilin Yao, Wenlong Yu, Ming Ye

“…To fully capture the spatiotemporal correlations, we propose a deep learning model based on graph convolutional neural networks called MDGCN. Firstly, we identify the heterogeneity of stations under two spaces by the Multi-graph convolutional layer. …”
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Enhanced Community Detection via Convolutional Neural Network: A Modified Approach Based on MRFasGCN Algorithm by Puneet Kumar, Dalwinder Singh, Mamoona Humayun, Ali Alqazzaz, Arun Malik, Ibrahim Alrashdi, Isha Batra, Ghadah Naif Alwakid

“…Initially, Newman and Girvan proposed traditional algorithms for community detection from social networks in 2004, but with the growth of social networks, Convolutional Neural Network (CNN) based algorithms are proposed by different researchers in recent years due to the inefficiency of traditional methods. …”
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Hybrid Convolutional Neural Network-Transformer Model for End-to-End Binaural Sound Source Localization in Reverberant Environments by Xinyi Chen, Lijia Zhao, Jie Cui, Hua Li, Xiaodong Wang

“…The WavLocT model has a unique feature extraction block that incorporates a convolutional neural network (CNN) and transformer structure, in which binaural localization features are extracted from different subband signal waveforms via the CNN structure. …”
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Gradual poisoning of a chest x-ray convolutional neural network with an adversarial attack and AI explainability methods by Stephen B. Lee

“…Abstract Given artificial intelligence’s transformative effects, studying safety is important to ensure it is implemented in a beneficial way. Convolutional neural networks are used in radiology research for prediction but can be corrupted through adversarial attacks. …”
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A Deep Learning Inversion Method for Airborne Time-Domain Electromagnetic Data Using Convolutional Neural Network by Xiaodong Yu, Peng Zhang, Xi Yu

“…In this paper, we present a deep learning inversion method that can be used to solve the fast inversion problem of airborne time-domain electromagnetic data; the method uses a one-dimensional convolutional neural network. The network structure consists of two parts containing different numbers of convolutional and pooling layers. …”
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A new framework for mental illnesses diagnosis using wearable devices aided by improved convolutional neural network by Hend S. Saad, John F. W. Zaki, Mohamed M. Abdelsalam

“…MHD diseases are difficult to be distinguished from each other because they come in many forms with different severity of symptoms and different periods of suffering. …”
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Intelligent Fault Diagnosis of Hydraulic System Based on Multiscale One-Dimensional Convolutional Neural Networks with Multiattention Mechanism by Jiacheng Sun, Hua Ding, Ning Li, Xiaochun Sun, Xiaoxin Dong

“…Subsequently, to effectively utilize the feature information of different frequencies, the HAM is integrated into the 1DCNN to form the MA-MS1DCNN. …”
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Vibration Signal-Based Fault Diagnosis of Rotary Machinery Through Convolutional Neural Network and Transfer Learning Method by Chirag Mongia, Shankar Sehgal

“…Initially, a deep learning approach utilizing convolutional neural networks (CNNs) has been employed to diagnose faults based on vibration data. …”
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