RDW-YOLO: A Deep Learning Framework for Scalable Agricultural Pest Monitoring and Control by Jiaxin Song, Ke Cheng, Fei Chen, Xuecheng Hua

“…Due to target diversity, life-cycle variations, and complex backgrounds, traditional pest detection methods often struggle with accuracy and efficiency. …”
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Advancing depth perception in spatial computing with binocular metalenses by Junkyeong Park, Gyeongtae Kim, Junsuk Rho

“…Liu et al. presents a compact binocular metalens-based depth perception system that integrates efficient edge detection through an advanced neural network. …”
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The advantages of k-visibility: A comparative analysis of several time series clustering algorithms by Sergio Iglesias-Perez, Alberto Partida, Regino Criado

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Research on an Apple Recognition and Yield Estimation Model Based on the Fusion of Improved YOLOv11 and DeepSORT by Zhanglei Yan, Yuwei Wu, Wenbo Zhao, Shao Zhang, Xu Li

“…This study introduces APYOLO, an enhanced apple detection algorithm based on an improved YOLOv11, integrated with the DeepSORT tracking algorithm to improve both detection accuracy and operational speed. …”
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A Novel Error Detection due to Joint CRC Aided Denoise-and-Forward Network Coding for Two-Way Relay Channels by Yulun Cheng, Longxiang Yang

“…In wireless two-way (TW) relay channels, denoise-and-forward (DNF) network coding (NC) is a promising technique to achieve spectral efficiency. However, unsuccessful detection at relay severely deteriorates the diversity gain, as well as end-to-end pairwise error probability (PEP). …”
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MEL-YOLO: A Novel YOLO Network With Multi-Scale, Effective, and Lightweight Methods for Small Object Detection in Aerial Images by Yang Yang, Fangtao Feng, Guisuo Liu, Juxing Di

“…Secondly, the improved model incorporates a decoupled detection head, which separates the classification task from the localization task, thereby improving detection accuracy while increasing detection complexity. …”
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A novel cluster of improved frilled lizard optimization and multi-ladder gated networks for the detection of cyber-attacks in computer networks by Vandana Dharmapuri, Sushama Rani Dutta

“…The proposed ML-GNUs are used for differentiating diverse attack patterns, and the improved frilled lizard technique is employed to tune the model’s hyper-parameters, reducing computational overhead and enhancing detection performance. The efficiency of the proposed model is assessed utilising both simulated real-time data traffic patterns and the CIC-IDS-2017 benchmark dataset, and standard performance metrics like accuracy, precision, recall, specificity, Matthews correlation coefficient (MCC), and F1-score are analyzed and measured. …”
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Linking Electrocardiogram and Echocardiogram: Comparing Classical Machine Learning and Deep Learning Neural Networks for the Detection of Regional Wall Motion Abnormalities by Shantanu M. Joshi, Hana R. Shaik, Shivam Rai Sharma, Philip Strong, Uma Srivatsa, Imo Ebong, Hyoyoung Jeong, Chen-Nee Chuah, Lihong Mo

“…Additionally, we compared the performance, training time and model complexity of 1D CNN model with the latest foundation model, HuBERT-ECG. …”
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YOLO-WTB: Improved YOLOv12n Model for Detecting Small Damage of Wind Turbine Blades From Aerial Imagery by Phat T. Nguyen, Duy C. Huynh, Loc D. Ho, Matthew W. Dunnigan

“…In addition, in the backbone part, we also propose to remove a Convolution module and an Area Attention Concatenate-Convolution-Fusion module and add an improved SoftPool Feature Spatial Pyramid Pooling - Fast module to increase the feature extraction ability while maintaining the complexity of the model. The proposed model not only optimizes wind turbine maintenance efficiency but also contributes to advancements in the field of computer vision.…”
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Enhanced detection of surface deformations in LPBF using deep convolutional neural networks and transfer learning from a porosity model by Muhammad Ayub Ansari, Andrew Crampton, Samer Mohammed Jaber Mubarak

“…Our approach demonstrates the power of transfer learning in adapting a model known for porosity detection in LPBF to identify surface deformations with high accuracy (94%), matching the performance of the best existing models but with significantly less complexity. …”
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Graphical Empirical Mode Decomposition–Convolutional Neural Network-Based Expert System for Early Corrosion Detection in Truss-Type Bridges by Alan G. Lujan-Olalde, Angel H. Rangel-Rodriguez, Andrea V. Perez-Sanchez, Martin Valtierra-Rodriguez, Jose M. Machorro-Lopez, Juan P. Amezquita-Sanchez

“…To enhance the computational efficiency of the method without compromising accuracy, different CNN architectures and image sizes are tested to propose a low-complexity model. …”
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No increase is detected and modeled for the seasonal cycle amplitude of <i>δ</i>¹³C of atmospheric carbon dioxide by F. Joos, F. Joos, S. Lienert, S. Lienert, S. Zaehle

“…We use isotope-enabled simulations of the Bern3D-LPX (Land surface Processes and eXchanges) Earth system model of intermediate complexity and fossil fuel emission estimates with a model of atmospheric transport to simulate atmospheric <span class="inline-formula"><i>δ</i>¹³</span>C<span class="inline-formula">_a</span> at globally distributed monitoring sites. …”
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Spot the bot: the inverse problems of NLP by Vasilii A. Gromov, Quynh Nhu Dang, Alexandra S. Kogan, Assel Yerbolova

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Automatic Segmentation and Characterization of Structure Planes From Borehole Images Based on Deep Learning by Shuangyuan Chen, Zengqiang Han, Yi Cheng, Chao Wang

“…By providing a reliable and efficient tool for structure plane segmentation and parameter characterization, this study enhances the accuracy and efficiency of rock mass structure detection and analysis.…”
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BEATS: Practical Audit Trail in Blockchain Systems by Bilal Alagha, Ilker Ozcelik

“…Results demonstrate that the RSA-based Cryptographic Accumulator significantly improves verification efficiency, achieving O(1) time and space complexity. …”
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Deep-Learning-Based Automated Building Construction Progress Monitoring for Prefabricated Prefinished Volumetric Construction by Wei Png Chua, Chien Chern Cheah

“…As manually processing high volumes of visual data can be extremely time consuming and tedious, building construction progress monitoring can be automated to be more efficient and reliable. However, the complex nature of construction sites and the presence of nearby infrastructure could occlude or distort visual data. …”
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Real-Time Detection of Milk Adulteration with a Portable Multispectral Analysis Device: A Multispectral Sensor and Optimized Logistic Regression Approach by Mahmut Durgun

“…Unlike complex neural network models, the logistic regression model offers simplicity, low power consumption, and efficient operation on microcontrollers. …”
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Single-index logistic model for high-dimensional group testing data by Changfu Yang, Wenxin Zhou, Wenjun Xiong, Junjian Zhang, Juan Ding

“…In this paper, we introduce a semi-parametric logistic single-index model for analyzing high-dimensional group testing data, which is particularly flexible in capturing complex nonlinear relationships. The proposed method achieves variable selection by parameter regularization, which proves especially beneficial for extracting relevant information from high-dimensional data. …”
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Rapid Qualitative Analysis of Cashmere and Wool Mixed Content Based on Improved XGBoost and SPA Using NIR Spectroscopy by Xin Chen, Fang Wang, Yaolin Zhu, Jinni Chen

“…After preprocessing the spectra using maximum–minimum normalization, a model is established based on the successive projection algorithm to select wavelengths. Validation results indicate that this model significantly can improve prediction accuracy and reduce operation time, providing a convenient, rapid, and efficient method for distinguishing between cashmere and wool content.…”
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RegCDNet: A RegNet-Based Framework for Remote Sensing Image Change Detection Combining Feature Enhancement and Gating Mechanism by Chuanlu Li, Xiaorong Xue, Caijia Zeng, Yifan Xu, Xingbiao Xu, Siyue Zhao

“…With the rapid development of remote sensing (RS) technology, it has become more and more convenient to obtain multi-temporal RS images, which provides new opportunities for the research and development of change detection (CD) technology. However, existing methods still have shortcomings in recognizing complex targets and accurately distinguishing the edges of change regions when performing CD in complex backgrounds. …”
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