Adaptive Disconnector States Diagnosis Method Based on Adjusted Relative Position Matrix and Convolutional Neural Networks by Peifeng Yan, Chenzhang Chang, Dong Hua, Haomin Huang, Suisheng Liu, Peiyi Cui

“…In this paper, we propose an HVD state diagnosis method featuring adaptive recognition capabilities based on Fault Difference Signals, Adjusted Relative Position Matrix and Convolutional Neural Networks (FDS-ARPM-CNN). …”
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A fault diagnosis method for rolling bearing based on gram matrix and multiscale convolutional neural network by Xinyan Zhang, Shaobin Cai, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…In this method, first, GM is used to reduce the noise of the collected vibration signals; Secondly, MSCNN is used for feature extraction, and the characteristics of vibration signals at different frequencies and time scales can be captured by the convolutional kernels of different scales; thirdly, two feature enhancement branches are added, utilizing the undenoised vibration signal as input, to enrich and diversify features while enhancing the model’s expressive and generalization capabilities; Finally, the experimental analysis was conducted on two bearing datasets to indicates that the noise robustness of GMSCNN is strong.…”
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SignFormer-GCN: Continuous sign language translation using spatio-temporal graph convolutional networks. by Safaeid Hossain Arib, Rabeya Akter, Sejuti Rahman, Shafin Rahman

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Multi-Signal Induction Motor Broken Rotor Bar Detection Based on Merged Convolutional Neural Network by Tianyi Wang, Shiguang Wen, Shaotong Sheng, Huimin Ma

“…This experiment investigates the detection of broken rotor bars of motors with different loads (25%, 50%, 75%, and 100% of rated load) and different fault levels (Normal, 1BRB, 2BRB, 3BRB, and 4BRB). …”
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A Novel Multi-Task and Ensembled Optimized Parallel Convolutional Autoencoder and Transformer for Speech Emotion Recognition by Zahra Sharifzadeh Jafari, Sanaz Seyedin

“…Recognizing the emotions from speech signals is very important in different applications of human-computer-interaction (HCI). …”
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Bearing fault diagnosis based on a multiple-constraint modal-invariant graph convolutional fusion network by Zhongmei Wang, Pengxuan Nie, Jianhua Liu, Jing He, Haibo Wu, Pengfei Guo

“…Multisensor data fusion method can improve the accuracy of bearing fault diagnosis, in order to address the problems of single-sensor data types and the insufficient exploration of redundancy and complementarity between different modal data in most existing multisensor data fusion methods for bearing fault diagnosis, a bearing fault diagnosis method based on a Multiple-Constraint Modal-Invariant Graph Convolutional Fusion Network (MCMI-GCFN) is proposed in this paper. …”
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A Dual-Branch Network of Strip Convolution and Swin Transformer for Multimodal Remote Sensing Image Registration by Kunpeng Mu, Wenqing Wang, Han Liu, Lili Liang, Shuang Zhang

“…In the upper branch of the dual-branch feature extraction module, we designed a combination of multi-scale convolution and Swin Transformer to fully extract features of remote sensing images at different scales and levels to better understand the global structure and context information. …”
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SNet: A novel convolutional neural network architecture for advanced endoscopic image classification of gastrointestinal disorders by Samra Siddiqui, Junaid A. Khan, Tallha Akram, Meshal Alharbi, Jaehyuk Cha, Dina A. AlHammadi

“…This step involves image resizing along with the augmentation step. The proposed convolutional neural network (CNN) model is comprised of six blocks placed at different layers. …”
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A fake news detection model using the integration of multimodal attention mechanism and residual convolutional network by Ying Lu, Naiwei Yao

“…Second, it designs a cross-modal alignment mechanism to better connect information across different data types. Third, it optimizes the feature fusion structure for more effective integration. …”
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Week-Ahead Water Demand Forecasting Using Convolutional Neural Network on Multi-Channel Wavelet Scalogram by Adithya Ramachandran, Hatem Mousa, Andreas Maier, Siming Bayer

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Effects of scale on segmentation of Nissl–stained rat brain tissue images via convolutional neural networks by Alexandro Arnal, Olac Fuentes

“…In this work, we test a fully convolutional architecture, U–Net, with Nissl–stained rat brain tissue images of different scales. …”
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CLASSIFICATION OF THE NUTRITIONAL CONDITION OF BEAN PLANTS (Phaseolus Vulgaris) USING CONVOLUTIONAL NEURAL NETWORKS AND IMAGE ANALYSIS by Julia Couto, Jamile Regazzo, Murilo Baesso, Adriano Tech, Thiago Silva

“…The images were processed and used to train and test different CNN configurations. The results indicated that larger sets of images and smaller blocks (10x10 pixels) increased accuracy, especially at 37 DAE. …”
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Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural Network by Jianhua Zhou, Pan Zheng, Shuaixing Wang, Shijing Wu, Xiaosun Wang

“…Experimental results show that the proposed method has better diagnostic accuracy and robustness than the BP neural network when the speed of training set data and test set data is different. This approach provides a reference for planetary gearbox fault diagnosis.…”
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Intelligent Fault Diagnosis of Bearing Based on Convolutional Neural Network and Bidirectional Long Short-Term Memory by Dazhang You, Linbo Chen, Fei Liu, YePeng Zhang, Wei Shang, Yameng Hu, Wei Liu

“…Then, the BLSTM is used to fuse the extracted features to acquire the failure information sufficiently and prevent the model from overfitting. Finally, two different experimental datasets are used to verify the effectiveness of the method. …”
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From data to dynamics: Reconstructing soliton collision phenomena in optical fibers using a convolutional autoencoder by Qibo Xu, Jifang Rong, Qilin Zeng, Xiaofang Yuan, Longnv Huang, Hua Yang

“…In this study, a convolutional autoencoder is constructed to extract and reconstruct the dynamical processes of soliton collisions in optical fibers. …”
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Finding the Optimal Convolutional Kernel Size for Semantic Segmentation of Pole-like Objects in Lidar Point Clouds by Z. Zhang, D. Shojaei, K. Khoshelham

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Three Dimensional Image Reconstruction of Electrical Capacitance Tomography Based on Improved ALEXNET Convolutional Neural Network by LI Yan, WANG Lu, LI Jiaqi

“…A method is proposed that the corresponding AlexNet neural network is trained according to the data of different flow patterns for the problem of slow sample training and low imaging accuracy for the threedimensional image reconstruction algorithm of convolutional neural networks. …”
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Few shot object detection for headdresses and seats in Thangka Yidam based on ResNet and deformable convolution by Hu Wenjin, Xue Panpan, He Guoyuan, Tang Huiyuan, Song Huafei, Yue Chaoyang

“…By introducing the offset of deformable convolution, the receptive field can adapt to the different sizes and shapes of the detection target of Thangka Yidam. …”
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Dynamic Tracking and Real-Time Fall Detection Based on Intelligent Image Analysis with Convolutional Neural Network by Ching-Bang Yao, Cheng-Tai Lu

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Enhanced Adaptive Wiener Filtering for Frequency-Varying Noise with Convolutional Neural Network-Based Feature Extraction by Chun-Lin Liao, Jian-Jiun Ding, De-Yan Lu

“…Noise appears in various forms, such as additive white Gaussian noise (AWGN) and Poisson noise across different frequencies. This study aims to denoise images without prior knowledge of the noise distribution. …”
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