Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs) by Robert A. Sowah, Kwaku Apeadu, Francis Gatsi, Kwame O. Ampadu, Baffour S. Mensah

“…Convolutional Neural Networks are mainstream methods of deep learning due to their ability to perform feature extraction and classification in the same architecture. …”
Get full text

DisasterAdaptiveNet: A robust network for multi-hazard building damage detection from very-high-resolution satellite imagery by Sebastian Hafner, Sebastian Gerard, Josephine Sullivan, Yifang Ban

“…Notably, several studies have proposed new network architectures and demonstrated their improved performance on xBD. …”
Get full text

Cyberbullying Detection, Prevention, and Analysis on Social Media via Trustable LSTM-Autoencoder Networks over Synthetic Data: The TLA-NET Approach by Alfredo Cuzzocrea, Mst Shapna Akter, Hossain Shahriar, Pablo García Bringas

“…Due to the fact that online social networks continue to daily expand, the proliferation of hate speech is also growing. …”
Get full text

APGCN-CF: A Spatio-Temporal-Aware Graph Convolutional Network Framework for Minor Agricultural Product Recommendation in Rural E-Commerce by Wenjin Hou, Ke Zhu, Pingzeng Liu, Honghua Jiang, Yan Zhang, Xinran Yu

“…Comprehensive experimental evaluations conducted on real-world minor agricultural product datasets, featuring scallions and garlic as representative cases, demonstrate that APGCN-CF consistently outperforms existing state-of-the-art baseline methods across multiple performance metrics, including precision, recall, and F1-score. …”
Get full text

A Comprehensive Method for Anomaly Detection in Complex Dynamic IoT Systems by Andrii Liashenko, Larysa Globa

“…These results underline the practical relevance of our approach for real-time monitoring of transportation networks, while also contributing theoretically to the integration of spatial and temporal features in anomaly detection.…”
Get full text

Continuous wave mud pulse data transmission method based on continuous gradation frequency keying modulation and Convolution neural network demodulation by Yingzhong Zhu, Zhenhua Xia, Yue Yang, Cihao Zhu, Guoqing Cai, Shuang Hu, Junhao Wang

“…This method employs Continuous Gradation Frequency Keying (CGFK) modulation combined with Convolution Neural Network (CNN) demodulation for continuous mud pulse data transmission. …”
Get full text

Advancing Alzheimer’s disease detection: a novel convolutional neural network based framework leveraging EEG data and segment length analysis by Md Nurul Ahad Tawhid, Siuly Siuly, Enamul Kabir, Yan Li

“…This framework contains EEG data collection, pre-processing for noise removal, temporal segmentation, convolutional neural network (CNN) model training and classification, and finally, evaluation. …”
Get full text

Hybrid convolutional neural network and bi-LSTM model with EfficientNet-B0 for high-accuracy breast cancer detection and classification by Umesh Kumar Lilhore, Yogesh Kumar Sharma, Brajesh Kumar Shukla, Muniraju Naidu Vadlamudi, Sarita Simaiya, Roobaea Alroobaea, Majed Alsafyani, Abdullah M. Baqasah

“…We propose a novel hybrid model that integrates Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory (Bi-LSTM) networks, and EfficientNet-B0, a pre-trained model. …”
Get full text

Res-LK-SLR: A Residual Network Based on Large Kernels and Shapelet-Level Representations for Spatial Infrared Spot Target Discrimination by Huiying Liu, Jiarong Wang, Weijun Zhong, Haitao Nie, Xiaotong Deng, Jiaqi Sun, Ming Zhu, Ming Wei

“…Thirdly, we propose a residual network Res-LK-SLR for IRS classification based on large kernels (LKs, providing long-term dependence) and shapelet-level representations (SLRs, where the hidden layer features are aligned with the learned high-level representations to obtain the optimal segmentation and generate shapelet-level representations). …”
Get full text

Forecasting of the Geomagnetic Activity for the Next 3 Days Utilizing Neural Networks Based on Parameters Related to Large‐Scale Structures of the Solar Corona by Tingyu Wang, Bingxian Luo, Jingjing Wang, Xianzhi Ao, Liqin Shi, Qiuzhen Zhong, Siqing Liu

“…To forecast SIR‐driven storms over longer horizons (3 days), a neural network model is constructed by incorporating coronal magnetic field physical parameters and the coronal hole features extracted from solar images (Pch). …”
Get full text

Study on the Anti-demyelination Mechanism of Bu-Shen-Yi-Sui Capsule in the Central Nervous System Based on Network Pharmacology and Experimental Verification by Zheng Zha, Yi-Jiang Liu, Si-Si Liu, Nan Zhang, Jun-Ling Li, Fang Qi, Liang-Yun Jin, Bing Xue, Tao Yang, Yong-Ping Fan, Hui Zhao, Lei Wang

“…The protein-protein interaction (PPI) network was constructed using bioinformatics methods. …”
Get full text

A spatio-temporal fusion-based approach for multi-dimensional classification of Parkinson’s disease progression using multi-modal dataset by Vinay Kukreja, Vandana Ahuja, Modafar Ati, Hariharan Shanmugasundaram, Murugaperumal Krishnamoorthy, Rishabh Sharma, Abhishek Bhattacherjee

“…Methods: By employing the fusing approach for structural medical resonance imaging (MRI) and dopamine transporter scan (DaTSCAN) along with clinical biomarker data to examine spatial and temporal relationships a fused feature representation was developed. PPMI dataset was employed for training and evaluation of the multi-task classification model with Cohen’s Kappa, cumulative link model (CLM), the area under the precision-recall curve (AUC-PR), and Brier score prominent evaluation metrics for analyzing the robustness of the model. …”
Get full text

SpecPT (Spectroscopy Pre-trained Transformer) Model for Extragalactic Spectroscopy. I. Architecture and Automated Redshift Measurement by Rohan Pattnaik, Jeyhan S. Kartaltepe, Clive Binu

Get full text

Monocular Vision-Based Depth Estimation of Forward-Looking Scenes for Mobile Platforms by Li Wei, Meng Ding, Shuai Li

“…Building on the foundational framework of <i>Monodepth2</i>, we introduce an intermediate module between the encoder and decoder of the depth estimation network to facilitate multiscale fusion of feature maps. …”
Get full text

AlexCapsNet: An Integrated Architecture for Image Classification With Background Noise by Muyi Bao, Nanlin Jin, Ming Xu

“…Capsule networks (CapsNet) are a pioneering architecture that can encode image features into vectors rather than scalars, addressing the limitations of traditional Convolutional Neural Networks (CNNs). …”
Get full text

Landslide Susceptibility Prediction Based on a CNN–LSTM–SAM–Attention Hybrid Model by Honggang Wu, Jiabi Niu, Yongqiang Li, Yinsheng Wang, Daohong Qiu

Get full text

Incident duration prediction through integration of uncertainty and risk factor evaluation: A San Francisco incidents case study. by Amirreza Salehi, Ardavan Babaei, Majid Khedmati

Get full text

Machine learning for the rElapse risk eValuation in acute biliary pancreatitis: The deep learning MINERVA study protocol by Mauro Podda, Adolfo Pisanu, Gianluca Pellino, Adriano De Simone, Lucio Selvaggi, Valentina Murzi, Eleonora Locci, Matteo Rottoli, Giacomo Calini, Stefano Cardelli, Fausto Catena, Carlo Vallicelli, Raffaele Bova, Gabriele Vigutto, Fabrizio D’Acapito, Giorgio Ercolani, Leonardo Solaini, Alan Biloslavo, Paola Germani, Camilla Colutta, Savino Occhionorelli, Domenico Lacavalla, Maria Grazia Sibilla, Stefano Olmi, Matteo Uccelli, Alberto Oldani, Alessio Giordano, Tommaso Guagni, Davina Perini, Francesco Pata, Bruno Nardo, Daniele Paglione, Giusi Franco, Matteo Donadon, Marcello Di Martino, Dario Bruzzese, Daniela Pacella

“…The ML model will utilise convolutional neural networks (CNN) for feature extraction and risk prediction. …”
Get full text

Polarization of road target detection under complex weather conditions by Feng Huang, Junlong Zheng, Xiancai Liu, Ying Shen, Jinsheng Chen

“…This module integrates channel-wise global self-attention and small kernel convolution to adaptively adjust the polarization enhancement method using dynamically extracted global and local polarization feature information. A multi-scale detection network is also designed to fully extract and fuse multi-scale feature information from receptive fields, channels, and spaces in different dimensions. …”
Get full text

Bearing fault diagnosis method based on SAVMD and CNN by SONG ChunSheng, LIANG YaRu, LU NiFang, DU Gang, JIA Bo

Get full text