Automated Icon Extraction from Tourism Maps: A Synergistic Approach Integrating YOLOv8x and SAM by Di Cao, Xinran Yan, Jingjing Li, Jiayao Li, Lili Wu

“…Nevertheless, the intricate shapes and dense distribution of symbols in tourist maps complicate the accurate and efficient detection and extraction using existing methods. …”
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Advances in Beneficiation Processes for Low-grade Bastnaesite-associated Fluorite Resources by Wei YANG, Hongqi TAN, Xiaohong XIA, Zhiyuan XIE, Yingjiang ZHU, Qiang GONG, Yue HU

“…In China, bastnaesite type fluorite resources are primarily formed in rare earth deposits such as the Bayan Obo and Maoniuping regions, characterized by "low-grade, fine-grained dissemination, and complex mineral paragenesis". Traditional separation technologies face challenges due to the similar floatability of rare earth minerals and fluorite, as well as the poor selectivity of conventional reagents. …”
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Papillary thyroid carcinoma whole-slide images as a basis for deep learning by M. V. Fridman, A. A. Kosareva, E. V. Snezhko, P. V. Kamlach, V. A. Kovalev

“…Authors discuss the second selection of signs for the marking of histological images, methodological approaches to dissect whole-slide images, how to prepare raw data for a future analysis. …”
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Swin-FSNet: A Frequency-Aware and Spatially Enhanced Network for Unpaved Road Extraction from UAV Remote Sensing Imagery by Jiwu Guan, Qingzhan Zhao, Wenzhong Tian, Xinxin Yao, Jingyang Li, Wei Li

“…However, unpaved roads often face challenges such as blurred boundaries, low contrast, complex shapes, and a lack of publicly available datasets. …”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

“…With the rapid advancements in deep learning, IoT intrusion detection systems have increasingly adopted deep learning models as the state-of-the-art solution due to their ability to handle complex data patterns. …”
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CAEB7-UNet: An Attention-Based Deep Learning Framework for Automated Segmentation of C-Spine Vertebrae in CT Images by Abhishek Kumar Pandey, Kedarnath Senapati, G. P. Pateel

“…This study presents a novel channel attention-based EfficientNetB7-UNet (CAEB7-UNet) method to address this complex task effectively. …”
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Unbiased analysis of obesity related, fat depot specific changes of adipocyte volumes and numbers using light sheet fluorescence microscopy. by Natalie Theobalt, Isabel Hofmann, Sonja Fiedler, Simone Renner, Georg Dhom, Annette Feuchtinger, Axel Walch, Martin Hrabĕ de Angelis, Eckhard Wolf, Rüdiger Wanke, Andreas Blutke

“…LSFM allows for accurate and efficient determination of relevant quantitative morphological adipocyte parameters. …”
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Biologically inspired hybrid model for Alzheimer’s disease classification using structural MRI in the ADNI dataset by Houmem Slimi, Imen Cherif, Sabeur Abid, Mounir Sayadi

“…Classification metrics (precision, recall, F1-score) highlight the model’s ability to disentangle complex spatiotemporal patterns in neurodegeneration. …”
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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…In recent years, the detection and analysis of near-fault pulse-like ground motions have become increasingly crucial due to their potential to cause significant structural damage during seismic events. …”
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IoT-Enhanced Smart Parking Management With IncepDenseMobileNet for Improved Classification by Xiaoxia Zheng, Wenxi Feng, Ning Wang, Huhemandula

“…The IncepDenseMobileNet (IDMN) model integrates Inception, DenseNet, and MobileNet architectures to proficiently capture complex patterns via multi-scale feature extraction and efficient depthwise separable convolutions. …”
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Chemometric and computational modeling of polysaccharide coated drugs for colonic drug delivery by Ahmad Khaleel AlOmari, Khaled Almansour

“…Parity plots and learning curves further validate MLP’s predictive reliability, demonstrating close alignment between actual and predicted values and efficient learning with minimal overfitting. Consequently, the MLP model emerges as the most effective approach for this predictive task, offering a robust tool for accurately modeling complex spectral data. …”
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Strategies and Challenges for Unmanned Aerial Vehicle-Based Continuous Inspection and Predictive Maintenance of Solar Modules by Ghulam E. Mustafa Abro, Amjad Ali, Sufyan Ali Memon, Tayab Din Memon, Faheem Khan

“…With the fast expansion of large-scale solar farms, the necessity for efficient and dependable maintenance and monitoring of solar modules has grown significantly. …”
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Large-Scale Demand Driven Design of a Customized Bus Network: A Methodological Framework and Beijing Case Study by Jihui Ma, Yang Yang, Wei Guan, Fei Wang, Tao Liu, Wenyuan Tu, Cuiying Song

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Research on the Real-Time Scoring of Chest Ring Target Based on Transfer Learning and Improved Lightweight Neural Network by Minghui Meng, Chuande Zhou

“…First, the Repvit-MobileNet block (re-parameterized depth wise separable mobile network module) is introduced into its backbone network to reduce model size and computational complexity while improving detection speed. Then, grouped shuffle convolution (GSConv) is used to reconstruct the standard down sampling convolutions in the PANFPN structure, promoting feature information extraction and fusion at bullet hole edges, reducing model computational complexity, and maintaining detection accuracy. …”
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HASSDE-NAS: Heuristic–Adaptive Spectral–Spatial Neural Architecture Search with Dynamic Cell Evolution for Hyperspectral Water Body Identification by Feng Chen, Baishun Su, Zongpu Jia

“…This approach outperforms existing methods in delineating narrow river systems and resolving water bodies with weak spectral contrast under complex backgrounds, such as vegetation or cloud shadows. …”
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On-site quantitative analysis of As(III) and As(V) in aqueous phase using portable laser-induced fluorescence platform by Lixia Feng, Qilong Bian, Shujun Wu, Tianyu Gao, Pei Zhang, Shujian Dai, Zebing Zeng, Sheng Xie

“…Here, a fluorogenic method is developed for the efficient detection of arsenite and arsenate ions using a portable platform directly in an aqueous phase. …”
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Enhancing Bottleneck Analysis in Ship Manufacturing with Knowledge Graphs and Large Language Models by Yanjun Ma, Tao Wu, Bin Zhou, Xiaoyang Liang, Jiwang Du, Jinsong Bao

“…This approach provides a scalable and efficient solution for analyzing complex bottleneck issues in industrial production, contributing to enhanced manufacturing efficiency and digital transformation.…”
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LeafDNet: Transforming Leaf Disease Diagnosis Through Deep Transfer Learning by Tofayet Sultan, Mohammad Sayem Chowdhury, Nusrat Jahan, M. F. Mridha, Sultan Alfarhood, Mejdl Safran, Dunren Che

“…These results emphasize the potential of this advanced deep learning framework as a scalable, efficient, and highly accurate solution for early plant disease detection, providing substantial benefits for plant health management and supporting sustainable agricultural practices.…”
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Intelligent Perception and Seam Tracking System for Thick Plate Weldments Based on Constant-Focus Optical Path by Lei Zhai, Wenze Ren, Fei Li, Rong Wu, Jinsong Lin, Jiahui Feng, Jun Zheng, Yang Liu

“…To achieve efficient and accurate thick plate welding, as well as to precisely extract and plan the paths of complex three-dimensional weld seams in large steel structures, this study introduces a novel vision-guided approach for robotic welding systems utilizing a constant-focus laser sensor. …”
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Secure Indoor Water Level Monitoring with Temporal Super-Resolution and Enhanced Yolov5 by Sui Guo, Jiazhi Huang, Yuming Yan, Peng Zhang, Benhong Wang, Houming Shen, Zhe Yuan

“…This module processes low-resolution water-level images to generate high-resolution outputs, thereby enabling reliable detection even in suboptimal conditions. Furthermore, unlike existing complex model-based approaches, our enhanced, lightweight Yolov5 model, featuring a small-scale feature mapping branch, ensures real-time monitoring and accurate detection across a variety of conditions, including daytime, nighttime, misty conditions, and wet surfaces. …”
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