LiDAR-Based Detection of Urban Trees Using a Backpack System by M. F. da Silva, L. F. Castanheiro, A. M. G. Tommaselli, A. M. G. Tommaselli, R. C. dos Santos, R. C. dos Santos, M. Galo, M. Galo

“…The sensor’s effective range is up to 50 m (at 80% reflectivity), enabling the acquisition of high-density point clouds at close-range distances while maintaining efficiency and accessibility in complex urban environments. …”
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AFHNet: Attention-Free Hybrid Network for Salient Object Detection in Underwater Images by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…However, traditional machine vision and deep learning approaches face notable challenges in complex underwater environments due to issues such as light attenuation, scattering, motion blur, color distortion, noise, low contrast, and multipath effects, which severely affect detection accuracy. …”
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RT-DETR-Smoke: A Real-Time Transformer for Forest Smoke Detection by Zhong Wang, Lanfang Lei, Tong Li, Xian Zu, Peibei Shi

“…Unlike generic object detection, smoke detection faces unique challenges due to smoke’s semitransparent, fluid nature, which often leads to false positives in complex backgrounds and missed detections—particularly around smoke edges and small targets. …”
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Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

“…Compared with existing detection methods, this approach shows outstanding performance in detection accuracy, localization precision, and computational efficiency, particularly excelling in small object detection.…”
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An Image-Free Single-Pixel Detection System for Adaptive Multi-Target Tracking by Yicheng Peng, Jianing Yang, Yuhao Feng, Shijie Yu, Fei Xing, Ting Sun

“…Conventional vision-based sensors face limitations such as low update rates, restricted applicability, and insufficient robustness in dynamic environments with complex object motions. Single-pixel tracking systems offer high efficiency and minimal data redundancy by directly acquiring target positions without full-image reconstruction. …”
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Seedling Stage Corn Line Detection Method Based on Improved YOLOv8 by LI Hongbo, TIAN Xin, RUAN Zhiwen, LIU Shaowen, REN Weiqi, SU Zhongbin, GAO Rui, KONG Qingming

“…However, traditional detection methods struggle to maintain high accuracy and efficiency under challenging conditions, such as strong light exposure and weed interference. …”
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Research on detection of wheat tillers in natural environment based on YOLOv8-MRF by Min Liang, Yuchen Zhang, Jian Zhou, Fengcheng Shi, Zhiqiang Wang, Yu Lin, Liang Zhang, Yaxi Liu

“…To bolster agricultural efficiency and precision, this study introduces the YOLOv8-MRF model (multi-path coordinate attention, receptive field attention convolution, and Focaler-CIoU-optimized YOLOv8), a groundbreaking advancement in automated detection of wheat tillers. …”
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Terahertz all-silicon metasurfaces with off-axis bifocal characteristics for polarization detection by Li Hui, Duan Shouxin, Zheng Chenglong, Xu Hang, Li Jie, Song Chunyu, Yang Fan, Shi Wei, Zhang Yating, Shen Yun, Yao Jianquan

“…The combination between all-silicon metasurfaces and focused beams carrying polarization information has offered a new opportunity for miniaturized polarization detection behavior. Here, we investigate and experimentally demonstrate a new scheme for realizing efficiently miniaturized polarization detection behavior based on the polarization multiplexing encoding technique. …”
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Gain efficiency with streamlined and automated data processing: Examples from high-throughput monoclonal antibody production. by Malwina Kotowicz, Magdalena Shumanska, Sven Fengler, Birgit Kurkowsky, Anja Meyer-Berhorn, Elisa Moretti, Josephine Blersch, Gisela Schmidt, Jakob Kreye, Scott van Hoof, Elisa Sánchez-Sendín, S Momsen Reincke, Lars Krüger, Harald Prüß, Philip Denner, Eugenio Fava, Dominik Stappert

“…Data management and sample tracking in complex biological workflows are essential steps to ensure necessary documentation and guarantee reusability of data and metadata. …”
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A lightweight weed detection model for cotton fields based on an improved YOLOv8n by Jun Wang, Zhengyuan Qi, Yanlong Wang, Yanyang Liu

“…Abstract In modern agriculture, the proliferation of weeds in cotton fields poses a significant threat to the healthy growth and yield of crops. Therefore, efficient detection and control of cotton field weeds are of paramount importance. …”
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Advances in the Application of Intelligent Algorithms to the Optimization and Control of Hydrodynamic Noise: Improve Energy Efficiency and System Optimization by Maosen Xu, Bokai Fan, Renyong Lin, Rong Lin, Xian Wu, Shuihua Zheng, Yunqing Gu, Jiegang Mou

“…Hydrodynamic noise is induced by hydrodynamic phenomena, such as pressure fluctuations, shear layers, and eddy currents, which have a significant impact on ship performance, pumping equipment efficiency, detection accuracy, and the living environment of marine organisms. …”
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Insertion/deletion polymorphisms in the ΔNp63 promoter are a risk factor for bladder exstrophy epispadias complex. by Simon Wilkins, Ke Wei Zhang, Istiak Mahfuz, Renaud Quantin, Nancy D'Cruz, John Hutson, Michael Ee, Darius Bagli, Karen Aitken, Fion Nga-Yin Fong, Patrick Kwok-Shing Ng, Stephen Kwok-Wing Tsui, Wendy Yin-Wan Fung, Tahmina Banu, Atul Thakre, Kaid Johar, Enrique Jaureguizar, Long Li, Wei Cheng

“…Bladder exstrophy epispadias complex (BEEC) is a severe congenital anomaly; however, the genetic and molecular mechanisms underlying the formation of BEEC remain unclear. …”
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Fibrin monomer complex on postoperative day 1 is correlated with the volume of deep vein thrombosis after knee surgery by Manabu Akagawa, Hiroaki Kijima, Yoshiaki Kimura, Hidetomo Saito, Kimio Saito, Ikuko Wakabayashi, Takeshi Kashiwagura, Naohisa Miyakoshi

“…It has not been identified how to efficiently detect high‐risk DVT while minimizing bleeding complications from anticoagulation. …”
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AN ITERATIVE ALGORITHM OF OBJECT DETECTION IN VIDEO SEQUENCE BASED ON HISTOGRAM SPATIAL MEASURES by I. A. Baryskievic

“…The parameters of algorithm are defined in terms of detection efficiency and computational complexity.…”
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High-Efficiency Enrichment of Megakaryocytes and Identification of Micromegakaryocytes from Human Bone Marrow by Imaging Flow Cytometry by Maya Nautrup Pedersen, Trine Engelbrecht Hybel, Jens Haugbølle Bjerre, Anne Sofie Borg Hammer, Anja Bille Bohn, Marie Bill, Carina Agerbo Rosenberg, Maja Ludvigsen

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Succinct Link Transformation-Based Overlapping Community Detection Framework for Social Network Analysis by Seungwoo Ryu, Sungsu Lim, Seungsoo Yoo, Sun Yong Kim

“…Within this transformed graph, edges and links are prioritized using minwise hashing, resulting in an efficient link transformation method. The proposed framework was evaluated against mainstream overlapping community detection algorithms. …”
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Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

“…This often leads to increased computational overhead and heightened complexity in detection models, potentially degrading overall system performance and efficiency. …”
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Towards real-time interest point detection and description for mobile and robotic devices by Patrick Rowsome, Muhammad Adil Raja, R. Muhammad Atif Azad

“…This paper demonstrates how techniques, developed for other CNN use cases, can be integrated into interest point detection and description systems to compress their network size and reduce the computational complexity; this reduces the barrier to their uptake in computationally challenged environments. …”
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A Multi-Domain Feature Fusion CNN for Myocardial Infarction Detection and Localization by Yunfan Chen, Jinxing Ye, Yuting Li, Zhe Luo, Jieqiang Luo, Xiangkui Wan

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Outlier detection algorithm based on fast density peak clustering outlier factor by Zhongping ZHANG, Sen LI, Weixiong LIU, Shuxia LIU

“…For the problem that peak density clustering algorithm requires human set parameters and high time complexity, an outlier detection algorithm based on fast density peak clustering outlier factor was proposed.Firstly, k nearest neighbors algorithm was used to replace the density peak of density estimate, which adopted the KD-Tree index data structure calculation of k close neighbors of data objects, and then the way of the product of density and distance was adopted to automatic selection of clustering centers.In addition, the centripetal relative distance and fast density peak clustering outliers were defined to describe the degree of outliers of data objects.Experiments on artificial data sets and real data sets were carried out to verify the algorithm, and compared with some classical and novel algorithms.The validity and time efficiency of the proposed algorithm are verified.…”
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