EEG Emotion Recognition Based on Temporal and Spatial Features of Sensitive signals by Zhihao Qu, Xiujuan Zheng

“…To solve the abovementioned problems, the authors proposed a method for emotion recognition based on long short-term memory (LSTM) neural network and convolutional neural network (CNN) combined with neurophysiological knowledge. …”
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3D Automatic Segmentation of Brain Tumor Based on Deep Neural Network and Multimodal MRI Images by Zhuliang Qian, Lifeng Xie, Yisheng Xu

“…The comparison of the results between the two algorithms proves that the CNN algorithm has the better processing power and higher efficiency.…”
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Fault Diagnosis of Planetary Gearbox Based on Motor Current Signal Analysis by Ziyuan Jiang, Qinkai Han, Xueping Xu

“…The convolutional neural network (CNN), which can automatically extract features, is also adopted. …”
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Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data by Nazir Jan, Nasru Minallah, Madiha Sher, Muhammad Wasim, Shahid Khan, Amal Al‐Rasheed, Hazrat Ali

“…Subsequently, we build a hybrid model combining deep CNN layers with a support vector machine (SVM). …”
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Learning deep forest for face anti-spoofing: An alternative to the neural network against adversarial attacks by Rizhao Cai, Liepiao Zhang, Changsheng Chen, Yongjian Hu, Alex Kot

“…Face anti-spoofing (FAS) is significant for the security of face recognition systems. neural networks (NNs), including convolutional neural network (CNN) and vision transformer (ViT), have been dominating the field of the FAS. …”
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Automatic Sleep Stage Classification Based on Convolutional Neural Network and Fine-Grained Segments by Zhihong Cui, Xiangwei Zheng, Xuexiao Shao, Lizhen Cui

“…Hence, we propose an automatic sleep stage classification method based on a convolutional neural network (CNN) combined with the fine-grained segment in multiscale entropy. …”
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SLG-Net: Small-Large-Global Feature-Based Multilevel Feature Extraction Network for Ultrasound Image Segmentation by Xinya Fan, Jianwen Hu, Kai Hu

“…The SLG-Net is parallel dual-encoder architecture which consists of a CNN encoder and a transformer encoder. Specifically, the CNN encoder improves the representation and interaction of fine feature and large-scale context feature for targets of different sizes by large-small kernel attention (LSKA) modules. …”
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Multitask Learning for Estimation of Magnetic Parameters Using Pattern Recognition by Anubha Sehgal, Shipra Saini, Hemkant Nehete, Kunal Kranti Das, Sourajeet Roy, Brajesh Kumar Kaushik

“…The custom CNN model performs best for the DMI constant and A_ex with R² scores of 0.991 and 0.998 respectively. …”
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Development of a Deep Learning‐Assisted Mobile Application for the Identification of Nematodes Through Microscopic Images by Naseeb Singh, Ashish Kumar Singh, L. K. Dhruw, Simardeep Kaur, S. Hazarika, K. K. Mishra, V. K. Mishra, Laxmi Kant

“…The CNN model was trained for 75 epochs using 70.0% of the nematode dataset, with validation on 20.0% of the dataset. …”
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Using machine learning-based models for personality recognition by Fatemeh Mohades Deilami, Hossein Sadr, Mozhdeh Nazari

“…Owing to the fact that various filter sizes in CNN may influence its performance, we decided to combine CNN with AdaBoost, a classical ensemble algorithm, to consider the possibility of using the contribution of various filter lengths and gasp their potential in the final classification via combining various classifiers with respective filter size using AdaBoost. …”
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A Novel AI-Based Integrated Cybersecurity Risk Assessment Framework and Resilience of National Critical Infrastructure by Sardar Muhammad Ali, Abdul Razzaque, Muhammad Yousaf, Sardar Sadaqat Ali

“…Additionally, the CNN, RNN, and SVM models achieved an accuracy of 98%. …”
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Novel transfer learning approach for hand drawn mathematical geometric shapes classification by Aneeza Alam, Ali Raza, Nisrean Thalji, Laith Abualigah, Helena Garay, Josep Alemany Iturriaga, Imran Ashraf

“…We introduced a novel machine-learning algorithm CnN-RFc that uses convolution neural networks (CNN) for spatial feature extraction and the random forest classifier for probabilistic feature extraction from image data. …”
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PlantAIM: A new baseline model integrating global attention and local features for enhanced plant disease identification by Abel Yu Hao Chai, Sue Han Lee, Fei Siang Tay, Hervé Goëau, Pierre Bonnet, Alexis Joly

“…Conventionally, detection has relied on plant pathologists, but recent advances in deep learning, particularly the Vision Transformer (ViT) and Convolutional Neural Network (CNN), have made it feasible for automated plant disease identification. …”
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Fast and accurate deep learning scans for signatures of natural selection in genomes using FASTER-NN by Sjoerd van den Belt, Nikolaos Alachiotis

“…We present FASTER-NN, a CNN classifier designed specifically for the precise detection of natural selection. …”
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Expression Recognition Method Using Improved VGG16 Network Model in Robot Interaction by Shengbin Wu

“…Finally, the expression recognition method combined with the improved VGG16 and CNN model is applied to the human-computer interaction of the NAO robot. …”
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Human Activity Recognition Using Graph Structures and Deep Neural Networks by Abed Al Raoof K. Bsoul

“…This research presents a novel HAR system combining graph structures with deep neural networks to capture both spatial and temporal patterns in activities. While CNN-based models excel at spatial feature extraction, they struggle with temporal dynamics, limiting their ability to classify complex actions. …”
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Attention-assisted dual-branch interactive face super-resolution network by Xujie Wan, Siyu Xu, Guangwei Gao

“…The Channel Attention Guidance Module (CAGM) refines CNN and Transformer fusion, ensuring precise facial detail restoration. …”
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Weather Radar Image Superresolution Using a Nonlocal Residual Network by Haoxuan Yuan, Qiangyu Zeng, Jianxin He

“…Inspired by the striking performance of the convolutional neural network (CNN) applied in feature extraction and nonlocal self-similarity of weather radar images, we proposed a nonlocal residual network (NLRN) on the basis of CNN. …”
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Speech Recognition System Based on Machine Learning in Persian Language by Shahed Mohammadi, Niloufar Hemati, Neda Mohammadi

“…The results showed 93% accuracy for the CNN classifier and 50% accuracy for testing the model with object detection.…”
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Deep learning-based system for prediction of work at height in construction site by Ibrahim Karatas

“…A total of 45 analyses were conducted using DNN, CNN, and LSTM deep-learning models, with 5 different window sizes and 3 different overlap rates. …”
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