Research on foreign object intrusion detection in railway tracks based on MSL-YOLO by Hongxia Niu, Dingchao Feng, Tao Hou

“…Specifically, a Multi-scale Shared Convolution Module (MSCM) is designed to replace SPPF, enhancing feature extraction while reducing parameters and computational cost. …”
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A High-Performance and Lightweight Maritime Target Detection Algorithm by Shidan Sun, Zhiping Xu, Xiaochun Cao, Jiachun Zheng, Jiawen Yang, Ni Jin

“…In the SFPF module, the ghost dynamic convolution combined with low-cost adaptive spatial feature fusion is proposed. …”
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Utilizing active learning and attention-CNN to classify vegetation based on UAV multispectral data by Sheng Miao, Chuanlong Wang, Guangze Kong, Xiuhe Yuan, Xiang Shen, Chao Liu

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HCT-Det: A High-Accuracy End-to-End Model for Steel Defect Detection Based on Hierarchical CNN–Transformer Features by Xiyin Chen, Xiaohu Zhang, Yonghua Shi, Junjie Pang

“…This structure combines window-based self-attention (WSA) blocks to reduce computational overhead and parallel residual convolutional (Res) blocks to enhance local feature continuity. …”
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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…Transfer learning strategies were applied to pre-train 8 convolutional neural networks (CNN). Performance was evaluated by mean accuracy, precision, recall, specificity, F1-score and area under the receiver operating characteristic (AUROC) values. …”
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A Multivariate Spatiotemporal Feature Fusion Network for Wind Turbine Gearbox Condition Monitoring by Shixian Dai, Shuang Han, Xinjian Bai, Zijian Kang, Yongqian Liu

“…SCADA data, due to their easy accessibility and low cost, have been widely applied in wind turbine gearbox condition monitoring. …”
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Anomaly Detection and Remaining Useful Life Prediction for Turbofan Engines with a Key Point-Based Approach to Secure Health Management by Yuntao Duan, Tao Zhang, Dunhuang Shi

“…The research method is based on convolution and the basic shape of convolution. Through feature fusion, a self-convolution operation, a half operation, and derivative operation on the original feature data of the engine, two key points of the engine in the entire lifecycle are obtained, and these key points are analyzed in detail. …”
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Lightweight interactive feature inference network for single-image super-resolution by Li Wang, Xing Li, Wei Tian, Jianhua Peng, Rui Chen

“…Abstract The emergence of convolutional neural network (CNN) and transformer has recently facilitated significant advances in image super-resolution (SR) tasks. …”
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FORECASTING STOCK PRICES FOR MARITIME SHIPPING COMPANY IN COVID-19 PERIOD USING MULTIVARIATE MULTI-STEP MULTI-STEP CONVOLUTIONAL NEURAL NETWORK - BIDIRECTIONAL LONG SHORT-TERM MEMO... by Ahmad GHAREEB, Mihai Daniel ROMAN

“…This study is intended to propose a predictive method based on Multivariate Multi-step convolutional neural network - Bidirectional Long Short-Term Memory (Multivariate Multi-step CNN-BiLSTM) networks in order to forecast the prices of three of the most prominent stocks of big organizations operating in maritime transport. …”
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A computational framework for processing time-series of earth observation data based on discrete convolution: global-scale historical Landsat cloud-free aggregates at 30 m spatial... by Davide Consoli, Leandro Parente, Rolf Simoes, Murat Şahin, Xuemeng Tian, Martijn Witjes, Lindsey Sloat, Tomislav Hengl

“…Processing large collections of earth observation (EO) time-series, often petabyte-sized, such as NASA’s Landsat and ESA’s Sentinel missions, can be computationally prohibitive and costly. Despite their name, even the Analysis Ready Data (ARD) versions of such collections can rarely be used as direct input for modeling because of cloud presence and/or prohibitive storage size. …”
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Identification of Ground Fissures in Mining Areas from UAV Images Based on RDC-UNet by Zhu Huashan

“…This study proposes an residual-depthwise separable convolution UNet (RDC-UNet) model to address these issues, building on U-Net by incorporating residual connections (RC), depthwise separable convolutions (DSC), and the convolutional block attention module (CBAM) attention mechanism. …”
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High-Precision and Low-Complexity Silicon Waveguide-Integrated Temperature Sensor System by Zhiming Zhang, Haole Kong, Yi Li

“…The waveguide layout is optimized through the finite-difference time-domain (FDTD) simulations, and a compressed taper structure improves the efficiency of speckle data collection while reducing the system complexity and cost. To achieve precise temperature demodulation, this paper employed a convolutional neural network (CNN) for nonlinear fitting. …”
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Quantization-Aware Training With Dynamic and Static Pruning by Sangho An, Jongyun Shin, Jangho Kim

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Prune and Distill: A Novel Knowledge Distillation Method for GCNs-Based Recommender Systems by Peng Yi, Zhaoxian Li, Lu Chen, Cheng Yang, Xiongcai Cai

“…Graph convolutional networks (GCNs)-based recommenders have demonstrated remarkable recommendation performances but suffer from prohibitive computational cost, limiting their practical deployment. …”
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Advanced Diabetic Retinopathy Detection with the R–CNN: A Unified Visual Health Solution by Sravya Valluri Sri, Srinivasu Parvathaneni Naga, Shafi Jana, Hołubowski Waldemar, Zielonka Adam

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Noise2Variance: Dual networks with variance constraint for self‐supervised real‐world image denoising by Hanlin Tan, Yu Liu, Maojun Zhang

“…Traditional methods utilizing convolutional neural networks (CNN) for denoising are trained using pairs of noisy and clean images to comprehend the transformation from a noisy image to a clean one. …”
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Decoding laying hen behavior and physiological status through acoustic biomarkers: temporal patterns, rooster-hen vocalization identification in group housing and environmental ada... by Xuanting Lin, Wanjun Zhu, Longshen Liu, Zhenlei Zhou

“…With the advancement of precision livestock farming (PLF), acoustic technology has emerged as a key tool for tracking the health and well-being of laying hens, owing to its non-invasive, real-time and cost-effective nature. In this study, continuous audio data were collected from commercial chicken houses over a period of 15 days, in addition to temperature and humidity index (THI) analysis, to develop a convolutional neural network (CNN)-based model for classifying chicken squawks. …”
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Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attenti... by Santosh Prabhakar Agnihotri, Mandar Padmakar Joshi

“…The methodology combines a Dandelion optimizer algorithm (DOA) for servo motor parameter optimization and an Attention pyramid convolution neural network (APCNN) (APCNN) for system behavior prediction. …”
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Novel Custom Loss Functions and Metrics for Reinforced Forecasting of High and Low Day-Ahead Electricity Prices Using Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM)... by Ziyang Wang, Masahiro Mae, Takeshi Yamane, Masato Ajisaka, Tatsuya Nakata, Ryuji Matsuhashi

“…To implement this, we integrate these custom loss functions into a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, augmented by an ensemble learning approach and multimodal features. …”
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EA-CNN: Enhanced attention-CNN with explainable AI for fruit and vegetable classification by Zeshan Aslam Khan, Muhammad Waqar, Khalid Mehmood Cheema, Ali Abu Bakar Mahmood, Quratul Ain, Naveed Ishtiaq Chaudhary, Abdullah Alshehri, Sultan S. Alshamrani, Muhammad Asif Zahoor Raja

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