ClipQ: Clipping Optimization for the Post-Training Quantization of Convolutional Neural Network by Yiming Chen, Hui Zhang, Chen Zhang, Yi Liu

Get full text

Analytical Comparison of Two Emotion Classification Models Based on Convolutional Neural Networks by Huiping Jiang, Demeng Wu, Rui Jiao, Zongnan Wang

“…Electroencephalography (EEG) is the measurement of neuronal activity in different areas of the brain through the use of electrodes. …”
Get full text

Hybrid Convolutional Neural Network for Localization of Epileptic Focus Based on iEEG by Linfeng Sui, Xuyang Zhao, Qibin Zhao, Toshihisa Tanaka, Jianting Cao

“…However, manual analysis and classification of the iEEG signal by clinicians are arduous and time-consuming and excessively depend on the experience. Due to individual differences of patients, the iEEG signal from different patients usually shows very diverse features even if the features belong to the same class. …”
Get full text

Novel Approach in Vegetation Detection Using Multi-Scale Convolutional Neural Network by Fatema A. Albalooshi

“…Moreover, the MSCNN architecture integrates multiple convolutional layers with varying kernel sizes (3 × 3, 5 × 5, and 7 × 7), enabling the model to extract features at different scales, which is vital for identifying diverse vegetation patterns across various landscapes. …”
Get full text

Intelligent Analysis of Hydraulic Concrete Vibration Time Based on Convolutional Neural Network by Hao Liu, Chengzhao Liu, Jiake Fu, Chenzhe Ma, Ye Zhang, Yumeng Lei

“…The system took the convolutional neural network as the basic framework, and divided the concrete vibration process into three different states: vibrating, not vibrating, and no vibration tube, realized the concrete vibration time through the analysis of concrete vibration video data. …”
Get full text

Leveraging Deep Learning and Convolutional Neural Network for Digital Waste Image Classification by Fauzan Naufal Anis, Sukmasetya Pristi, Nuryanto Nuryanto

Get full text

Gearbox fault diagnosis convolutional neural networks with multi-head attention mechanism by Xu Hang, Li Huawei, Yang Shufeng, Cui Jianghong, Li Youhua, He Yuanchun, Xie Guiping, Wu Yaoting

“…Then, the multi-head attention mechanism was incorporated to focus on different feature spaces and obtain diverse feature information. …”
Get full text

Convolutional neural network analysis of optical texture patterns in liquid-crystal skyrmions by J. Terroa, M. Tasinkevych, C. S. Dias

“…Machine learning can also be employed to identify phase transitions and classify different liquid crystalline phases and topological defects. …”
Get full text

Partial Discharge Pattern Recognition of Switchgear Based on Residual Convolutional Neural Network by Xueyou HUANG, Jun XIONG, Yu ZHANG, Hui LIU, Lu CHEN, Xianglin MENG, Xiuchen JIANG

“…Based on the partial discharge simulation experiments of different insulation defect categories of switchgears and the field testing of distribution stations, a sample database of switchgear partial discharge data is constructed, and experimental analysis is conducted. …”
Get full text

Balancing Complexity and Performance in Convolutional Neural Network Models for QUIC Traffic Classification by Giovanni Pettorru, Matteo Flumini, Marco Martalò

“…To this end, the research community has turned its attention to statistical analysis and Machine Learning (ML). In particular, Convolutional Neural Networks (CNNs) are gaining momentum in the research community for ML-based NTC leveraging statistical analysis of flow characteristics. …”
Get full text

STFGCN: Spatio-Temporal Fusion Graph Convolutional Networks for Subway Traffic Prediction by Xiaoxi Zhang, Zhanwei Tian, Yan Shi, Qingwen Guan, Yan Lu, Yujie Pan

“…Furthermore, we introduce trend similarity-aware attention to capture the evolutionary trends of time series and adopt a dynamic correlation graph convolutional network to dynamically adjust spatial correlation strengths based on changes in different time periods. …”
Get full text

Unsupervised Structural Damage Detection Technique Based on a Deep Convolutional Autoencoder by Zahra Rastin, Gholamreza Ghodrati Amiri, Ehsan Darvishan

“…Most of the deep learning-based methods proposed for damage detection in civil structures are based on supervised algorithms that require data from the healthy state and different damaged states of the structure in the training phase. …”
Get full text

Advancements in Plant Pests Detection: Leveraging Convolutional Neural Networks for Smart Agriculture by Gopalakrishnan Nagaraj, Dakshinamurthy Sungeetha, Mohit Tiwari, Vandana Ahuja, Ajit Kumar Varma, Pankaj Agarwal

“…We developed a convolutional neural network (CNN)-based framework for identifying pest-borne diseases in tomato leaves using the Plant Village Dataset and the MobileNetV2 architecture. …”
Get full text

Pesticide Residue Detection in Broccoli Based on Hyperspectral Technology and Convolutional Neural Network by Dan WANG, Yuqing LUAN, Zuojun TAN, Wei WEI

“…A one-dimensional convolutional neural network (1D-CNN) model was established using raw spectral data, which achieved recognition accuracy of 94.29%, 95.71%, 94.29%, and 97.14% for high-efficiency cypermethrin, chlorpyrifos, imidacloprid, and water, all of which were higher than the SVM model. …”
Get full text

Time–Frequency Transformations for Enhanced Biomedical Signal Classification with Convolutional Neural Networks by Georgios Lekkas, Eleni Vrochidou, George A. Papakostas

“…<b>Background:</b> Transforming one-dimensional (1D) biomedical signals into two-dimensional (2D) images enables the application of convolutional neural networks (CNNs) for classification tasks. …”
Get full text

Traffic Scene Depth Analysis Based on Depthwise Separable Convolutional Neural Network by Jianzhong Yuan, Wujie Zhou, Sijia Lv, Yuzhen Chen

“…The output from all different blocks is combined afterwards. Finally, transposed convolution layers were used for upsampling the feature maps to the same size with the original RGB image. …”
Get full text

Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…The attention-based convolutional recurrent neural network (ACRNN) can reconstruct a representative sample of reservoir rocks. …”
Get full text

Automatic melanoma detection using an optimized five-stream convolutional neural network by Vida Esmaeili, Mahmood Mohassel Feghhi, Hadi Seyedarabi

“…These challenges include the lack of a balanced dataset, high variability within melanoma lesions, differences in the locations of skin lesions in images, the similarity between different skin lesions, and the presence of various artifacts. …”
Get full text

Authorship Classification in a Resource Constraint Language Using Convolutional Neural Networks by Md. Rajib Hossain, Mohammed Moshiul Hoque, M. Ali Akber Dewan, Nazmul Siddique, Md. Nazmul Islam, Iqbal H. Sarker

“…Using three text embedding techniques (Word2Vec, GloVe and FastText) and combinations of different hyperparameters, 90 embedding models are created in this study. …”
Get full text

Hyperspectral Band Selection via Heterogeneous Graph Convolutional Self-Representation Network by Junde Chen, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

“…In addition, they handle each HSI as an integrated unit to harness implicit spatial information, disregarding spatial distribution variations across different homogeneous regions. To fully leverage structural information, this study introduces a novel BS method, termed the dual heterogeneous graph convolutional network with enhanced self-representation (ESR-HGCN), for HSI BS. …”
Get full text