Effects of Hybridizing the U-Net Neural Network in Traffic Lane Detection Process by Aron Csato, Florin Mariasiu

“…Similarly, in the Carla dataset (known for the complexity of the generated images), a substantial improvement was recorded, with an increase of +8.0% in mIoU and +5.7% in F1 score, showing better adaptability of the model to geometric structures in complex images. …”
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Research on object detection and recognition in remote sensing images based on YOLOv11 by Lu-hao He, Yong-zhang Zhou, Lei Liu, Wei Cao, Jian-hua Ma

“…Abstract This study applies the YOLOv11 model to train and detect ground object targets in high-resolution remote sensing images, aiming to evaluate its potential in enhancing detection accuracy and efficiency. …”
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Rice disease detection method based on multi-scale dynamic feature fusion by Qian Fan, Runhao Chen, Bin Li

“…In order to enhance the accuracy of rice leaf disease detection in complex farmland environments, and facilitate the deployment of the deep learning model onto mobile terminals for rapid real-time inference, this paper introduces a disease detection network titled YOLOv11 Multi-scale Dynamic Feature Fusion for Rice Disease Detection (YOLOv11-MSDFF-RiceD). …”
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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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Improved YOLOv8n Models for Object Detection in Remote Sensing Images by Young-Long Chen, Kai-Chun Hung, Jia-Yun Zhang, Ling-Wei Lin

“…However, applying these models to remote sensing images remains challenging due to complex backgrounds, high object scale variation, and the difficulty of detecting small objects. …”
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A policy conflict detection mechanism for multi-controller software-defined networks by You Lu, Qiming Fu, Xuefeng Xi, Zhenping Chen, Encen Zou, Baochuan Fu

“…The experimental results under the campus network environment prove that our method can effectively detect the conflict of flow policies existing in the multi-controller software-defined network and has advantages over the existing methods in the integrity, accuracy, and efficiency of the detection.…”
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Detecting eavesdropping nodes in the power Internet of Things based on Kolmogorov-Arnold networks. by Rong Wang, Weibin Jiang, Yanjin Shen, Qiqing Yue, Kan-Lin Hsiung

“…Traditional eavesdropping detection methods struggle to adapt to complex and dynamic attack patterns, necessitating the exploration of more intelligent and efficient anomaly localization approaches. …”
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Advances in research on novel technologies for the detection of exogenous contaminants in traditional Chinese medicine by Ziyu Guo, Junyao Li, Lina Zeng, Ping Wang, Meifang Li, Chang Su, Shuhong Wang

“…Exogenous contaminants in traditional Chinese medicine (TCM), including pesticide residues, heavy metals, mycotoxins, and sulfur dioxide residues, pose significant risks to human health and environmental safety. Conventional detection methods are limited by insufficient sensitivity, complex sample preparation, and challenges in multi-residue analysis, compromising accuracy and efficiency. …”
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DeepAT: A Deep Learning Wheat Phenotype Prediction Model Based on Genotype Data by Jiale Li, Zikang He, Guomin Zhou, Shen Yan, Jianhua Zhang

“…This provides a data-driven selection criterion for genomic selection, making the selection process more efficient and targeted. …”
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CP-YOLO: An Algorithm for Cigarette Pack Defects Detection Based on CCD Images by Peng Dong, Weihua Feng, Rui Wang, Mingyan Zhang, Qunye Hong, Yongsheng Wang, Di Wang, Guohao Zong

“…The failure to detect defective packs promptly may affect production efficiency and material consumption. …”
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Indocyanine Green and Arginine-Glycine-Aspartic Acid Complex Used in Intraoperative Visualization during Resection of Bladder Tumour by Li Peng, I. R. Kabirov, A. R. Kasinskaya, Jiaqi Wang, Wanhai Xu, E. K. Zhuk, R. A. Nuralieva

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Ensemble learning for multi-class COVID-19 detection from big data. by Sarah Kaleem, Adnan Sohail, Muhammad Usman Tariq, Muhammad Babar, Basit Qureshi

“…Although existing techniques are useful for detecting COVID-19 using X-rays, there is a need for further improvement in efficiency, particularly in terms of training and execution time. …”
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Lightweight Pyramid Cross-Attention Network for No-Service Rail Surface Defect Detection by Sixu Guo, Jiyou Fei, Liying Wang, Hua Li, Xiaodong Liu

“…Vision-based rail defect detection plays a crucial role in ensuring the safety and efficiency of railway transportation systems. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…First, a channel and spatial attention mechanism is introduced to improve the network’s capability to extract target features, significantly enhancing grasp detection performance in complex backgrounds. Second, an efficient attention module search strategy is proposed to replace traditional fully connected layer structures, which not only increases detection accuracy but also reduces computational overhead. …”
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An Enhanced DCO-OFDM Scheme for Dimming Control in Visible Light Communication Systems by Yang Yang, Zhimin Zeng, Julian Cheng, Caili Guo

“…Furthermore, two parameter selection mechanisms with different complexities and performance gains are designed for the piecewise function in the eDCO-OFDM scheme. …”
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CRITERIA FOR SELECTION OF ALLOYING COMPONENTS AND BASE COMPOSITIONS FOR MANUFACTURING OF MECHANICALLY ALLOYED DISPERSION-STRENGTHENED MATERIALS ON THE BASIS OF METALS by F. G. Lovshenko, G. F. Lovshenko

“…Experimental investigations have shown that an optimum complex of mechanical properties is obtained in the case when nano-sized strengthening phase is equal to 3–5 % (volume). …”
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Crashing Fault Residence Prediction Using a Hybrid Feature Selection Framework from Multi-Source Data by Xiao Liu, Xianmei Fang, Song Sun, Yangchun Gao, Dan Yang, Meng Yan

“…This task plays a crucial role in software quality assurance by enhancing debugging efficiency and reducing testing costs. This study introduces SCM, a two-stage composite feature selection framework designed to address this challenge. …”
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Vehicle detection and classification for traffic management and autonomous systems using YOLOv10 by Anning Ji, Xintao Ma

“…Our approach leverages the advantages of each method to enhance detection accuracy and efficiency, especially in complex traffic scenarios. …”
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Detecting Alzheimer's Based on MRI Medical Images by Using External Attention Transformer by Farrel Ardannur Deswanto, Isman Kurniawan

“…It enhances image classification by using two shared external memories and an attention mechanism that filters out redundant information for improved performance and efficiency. The aim of this research is to evaluate and compare the performance of the baseline Convolutional Neural Network (CNN) model, the Vision Transformer (ViT) model, and the EAT model in detecting Alzheimer's using a dataset of 6400 brain MRI images. …”
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Implementation of Fuzzy Multiple Attribute Decision Making (FMADM) and Simple Additive Weighting (SAW) for Selecting the Best Stocks by Saddam Ali Habibie Nasution, Sriani Sriani

“…Such analysis involves various complex financial indicators. This study combines the Fuzzy Multiple Attribute Decision Making (FMADM) method and the Simple Additive Weighting (SAW) method to assist investors in selecting the best stocks in the banking sector. …”
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