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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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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Spot the bot: the inverse problems of NLP by Vasilii A. Gromov, Quynh Nhu Dang, Alexandra S. Kogan, Assel Yerbolova

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Training a convolutional neural network for exoplanet classification with transit photometry data by Juliana Wang

“…As a result, efforts to enhance the efficiency of exoplanet research have led to the development of various detection methods, including transit photometry. …”
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A High-Precision Defect Detection Approach Based on BiFDRep-YOLOv8n for Small Target Defects in Photovoltaic Modules by Yi Lu, Chunsong Du, Xu Li, Shaowei Liang, Qian Zhang, Zhenghui Zhao

“…However, latent faults emerging from the long-term operation of photovoltaic (PV) power plants significantly compromise their operational efficiency. The existing EL detection methods in PV plants face challenges including grain boundary interference, probe band artifacts, non-uniform luminescence, and complex backgrounds, which elevate the risk of missing small defects. …”
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Enhanced AUV Autonomy Through Fused Energy-Optimized Path Planning and Deep Reinforcement Learning for Integrated Navigation and Dynamic Obstacle Detection by Kaijie Zhang, Yuchen Ye, Kaihao Chen, Zao Li, Kangshun Li

“…This fusion significantly advances the integration of navigation with dynamic obstacle detection. Ultimately, it enhances AUV operational performance and autonomy in complex maritime scenarios.…”
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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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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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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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Enhancing Wheat Spike Counting and Disease Detection Using a Probability Density Attention Mechanism in Deep Learning Models for Precision Agriculture by Ruiheng Li, Wenjie Hong, Ruiming Wu, Yan Wang, Xiaohan Wu, Zhongtian Shi, Yifei Xu, Zixu Han, Chunli Lv

“…By combining the probability density attention mechanism and the density loss function, the proposed model significantly improves the detection accuracy and efficiency, offering important references for future related research.…”
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Rapid Detection of Trace Toxicants in Blood Using Thermal Desorption Coupled to Continuous Atmospheric Pressure Interfaced Ion Trap Mass Spectrometry by Hui-wen RUAN, Gui-yun SONG, Zhi-gang FAN, Suo-suo YANG, Jian KANG, Lei HUA, Wei-guo WANG

“…In addition, combined with simple and efficient liquid-liquid extraction, the rapid and accurate detection of toxicants in blood was achieved within 2 min. …”
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FIDC-YOLO: Improved YOLO for Detecting Pine Wilt Disease in UAV Remote Sensing Images via Feature Interaction and Dependency Capturing by Zekun Xu, Yipeng Zhou, Shiting Wen, Weipeng Jing

“…Uncrewed aerial vehicle (UAV) remote sensing technology has been widely applied in pine wilt disease (PWD) detection. UAV-collected PWD images are characterized by complex backgrounds, small target sizes, and uneven spatial distribution. …”
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A Comparative Study of Two-Stage Intrusion Detection Using Modern Machine Learning Approaches on the CSE-CIC-IDS2018 Dataset by Isuru Udayangani Hewapathirana

“…The findings emphasize the complementary nature of the two approaches, suggesting that a combined model could achieve a balance between accuracy and computational efficiency. This work provides valuable insights for designing scalable, high-performance intrusion detection systems in modern network environments.…”
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Determination of Nitrofuran Metabolites in Complex Food Matrices Using a Rough, Cheap, Easy-Made Wooden-Tip-Based Solid-Phase Microextraction Probe and LC-MS/MS by Xiaoming Gong, Kai Li, Wenjuan Xu, Liming Jin, Mengxiao Liu, Mengmeng Hua, Guoning Tian

“…In addition, the main parameters affecting the SPME procedure efficiency were investigated in detail and the optimal conditions were found. …”
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A Novel Training Strategy for Deep Learning Model Compression Applied to Automatic Modulation Classification by Mateus A. Goldbarg, Micael Balza, Sergio N. Silva, Lucileide M. D. Silva, Marcelo A. C. Fernandes

“…This research represents a significant advancement towards the practical deployment of deep learning in modulation classification systems, paving the way for enhanced efficiency and performance in wireless communication technologies.…”
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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…This paper proposes a railway worker detection method based on improved support vector machines (ISVM), while using non-local mean noise reduction and histogram equalisation pre-processing techniques to optimise image quality to improve detection efficiency and accuracy. …”
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Effectiveness and optimization of bidirectional long short-term memory (BiLSTM) based fast detection of deep fake face videos for real-time applications by Haoxiang Wang

“…The aim is to overcome the limitations of current technologies in terms of efficiency and accuracy. An optimized BiLSTM architecture and training strategy are employed, enhancing recognition capabilities through data preprocessing and feature enhancement while also minimizing computational complexity and resource consumption during detection. …”
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Passive Radar Low Slow Small Detection Dataset (LSS-PR-1.0) and Multi-domain Feature Extraction and Analysis Methods by Xiaolong CHEN, Guilin RAO, Jian GUAN, Jinhao WANG, Hongyong WANG, Caisheng ZHANG, Jianxin YI, Xianrong WAN, Yunhua RAO

“…Due to the uncontrollable source of passive radar signal radiations, target characteristics are more complex, which makes target detection and identification extremely difficult. …”
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DETECTION OF METALLIC AND NON-METALLIC ORIGIN FOREIGN BODIES IN BIOLOGICAL TISSUES OBTAINED AS A RESULT OF MILITARY TRAUMA: A LITERATURE REVIEW by Viktor A. Chernyak, Dmytro Ye. Dubenko, Kostiantyn K. Karpenko, Lidiia V. Butska, Vitalii S. Myrona, Nataliia Yu. Kondratiuk

“…Development of new imaging techniques: Development of non-radioactive fragments detection in gunshot wounds using noise emission technology, imaging and intraoperative navigation will increase the efficiency of detection and treatment of patients with FB.…”
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A Consensus-Driven Distributed Moving Horizon Estimation Approach for Target Detection Within Unmanned Aerial Vehicle Formations in Rescue Operations by Salvatore Rosario Bassolillo, Egidio D’Amato, Immacolata Notaro

“…This paper proposes a Distributed Moving Horizon Estimation (DMHE) technique that integrates consensus theory and Moving Horizon Estimation to optimize computational efficiency, minimize communication requirements, and enhance system robustness. …”
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