Remaining Useful Life Prediction of Rolling Bearings Based on Multiscale Convolutional Neural Network with Integrated Dilated Convolution Blocks by Ran Wang, Ruyu Shi, Xiong Hu, Changqing Shen

“…Convolution filters with different dilation rates are integrated to form a dilated convolution block, which can learn features in different receptive fields. …”
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ST-CFI: Swin Transformer with convolutional feature interactions for identifying plant diseases by Sheng Yu, Li Xie, Liang Dai

“…The ST-CFI model effectively integrates the strengths of the Convolutional Neural Networks (CNNs) and Swin Transformers, enabling the extraction of both local and global features from plant images. …”
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EFCNet: Expert Feature-Based Convolutional Neural Network for SAR Ship Detection by Zheng Chen, Yuxiang Zhang, Jing Bai, Biao Hou

“…In this paper, we revisit the relationship between SAR expert features and network abstract features, and propose an expert-feature-based convolutional neural network (EFCNet). …”
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Blind Recognition of Convolutional Codes Based on the ConvLSTM Temporal Feature Network by Lu Xu, Yixin Ma, Rui Shi, Juanjuan Li, Yijia Zhang

“…To tackle this problem, we propose ConvLSTM-TFN (temporal feature network), an innovative blind-recognition network that integrates convolutional layers, long short-term memory (LSTM) networks, and a self-attention mechanism. …”
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Underwater object detection algorithm integrating image enhancement and deformable convolution by Lijia Guo, Xiangchun Liu, Dongsheng Ye, Xuebao He, Jianxin Xia, Wei Song

“…In addition, the separated and enhancement attention module (SEAM) is integrated to better capture features of occluded targets. …”
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A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

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Integration of Convolutional Neural Network and Image Processing for Pulp Fibril Detection and Measurement by Tanachot Chirakitsakul, Pakaket Wattuya, Phichit Somboon, Panthira Jansakra, Chakrit Watcharopas

“…This study proposes a novel method that integrates deep learning with image processing techniques to automate fibril detection and fibrillation index computation. …”
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PIONet: A Positional Encoding Integrated Onehot Feature-Based RNA-Binding Protein Classification Using Deep Neural Network by Mahmood A. Rashid, Mayank Chaturvedi, Kuldip K. Paliwal

“…Here we present PIONet, a deep learning method based on a convolutional neural network (CNN) that accurately classifies RBPs. …”
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Dental bur detection system based on asymmetric double convolution and adaptive feature fusion by HongLing Hou, Ao Yang, Xiangyao Li, Kangkai Zhu, Yandi Zhao, Zhiqiang Wu

“…A Lightweight Asymmetric Dual Convolution module (LADC) was devised to diminish the detrimental effects of extraneous features on the model’s precision, thereby enhancing the feature extraction network. …”
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A Multi-Scale Feature Fusion Hybrid Convolution Attention Model for Birdsong Recognition by Lianglian Gu, Guangzhi Di, Danju Lv, Yan Zhang, Yueyun Yu, Wei Li, Ziqian Wang

“…To address this issue, we propose a multi-scale hybrid convolutional attention mechanism model (MUSCA). This method combines depthwise separable convolution and traditional convolution for feature extraction and incorporates self-attention and spatial attention mechanisms to refine spatial and channel features, thereby improving the effectiveness of multi-scale feature extraction. …”
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Spatiotemporal wind speed forecasting using conditional local convolution and multidimensional meteorology features by Meng Wang, Juanle Wang, Mingming Yu, Fei Yang

“…This model addresses uniform influence model weight issue by redesigning convolution kernels to better capture local meteorological features and integrating multiple influencing factors. …”
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Graph convolution-based adaptive feature fusion method for MRI brain tumor segmentation by Ye ZHANG, Muqing ZHANG, Xuegang YUAN, Datian NIU

“…The algorithm was based on 3D U-Net,incorporating a graph convolution inference module to capture additional long-range contextual features. …”
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An XAI Approach to Melanoma Diagnosis: Explaining the Output of Convolutional Neural Networks with Feature Injection by Flavia Grignaffini, Enrico De Santis, Fabrizio Frezza, Antonello Rizzi

“…This field is still unexplored; thus, in this paper, we aim to provide a method to explain, qualitatively and quantitatively, a convolutional neural network model with feature injection for melanoma diagnosis. …”
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Diagnosis of abnormal sound in loudspeakers by integrated attention mechanism convolutional neural network by ZHOU Jinglei, WANG Xiaoming, LI Limin

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Photonic neuromorphic accelerator for convolutional neural networks based on an integrated reconfigurable mesh by Aris Tsirigotis, George Sarantoglou, Stavros Deligiannidis, Erica Sánchez, David Sanchez, Ana Gutierrez, Adonis Bogris, Jose Capmany, Charis Mesaritakis

“…On the other hand, upscaling integrated photonic circuits to meet the demands of state-of-the-art machine learning schemes such as convolutional layers, remains challenging. …”
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YOLO-CSMD: Integrating Improved Convolutional Techniques for Manhole Cover Defect Detection by Zhiwang Xu, Haowei Luo, Huijie Zhu, Wanfa Sun, Shengying Yang

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Liver Tumor Prediction using Attention-Guided Convolutional Neural Networks and Genomic Feature Analysis by S. Edwin Raja, J. Sutha, P. Elamparithi, K. Jaya Deepthi, S.D. Lalitha

“…To overcome these hurdles, this study presents two integrated approaches namely, – Attention-Guided Convolutional Neural Networks (AG-CNNs), and Genomic Feature Analysis Module (GFAM). …”
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Classification of multi-lead ECG based on multiple scales and hierarchical feature convolutional neural networks by Feiyan Zhou, Duanshu Fang

“…However, current deep learning-based classification methods often encounter difficulties in effectively integrating both the morphological and temporal features of Electrocardiograms (ECGs). …”
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DAF-UNet: Deformable U-Net with Atrous-Convolution Feature Pyramid for Retinal Vessel Segmentation by Yongchao Duan, Rui Yang, Ming Zhao, Mingrui Qi, Sheng-Lung Peng

“…However, the inherent challenges posed by the complex geometries of vessels and the highly imbalanced distribution of thick versus thin vessel pixels demand innovative solutions for robust feature extraction. In this paper, we introduce DAF-UNet, a novel architecture that integrates advanced modules to address these challenges. …”
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Classification of Pulmonary Nodules Using Multimodal Feature‐Driven Graph Convolutional Networks with Specificity Proficiency by Renjie Xu, Zhanlue Liang, Dan Wang, Rui Zhang, Jiayi Li, Lingfeng Bi, Kai Zhang, Weimin Li

“…Compared with radiomics and clinical feature‐based machine learning methods, whether a graph convolutional neural network (GCNN) based on radiomics and clinical features improve the performance in distinguishing benign and malignant pulmonary nodules is not well studied. …”
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