MHFS-FORMER: Multiple-Scale Hybrid Features Transformer for Lane Detection by Dongqi Yan, Tao Zhang

“…Furthermore, a significant drawback of most existing lane-detection algorithms lies in their reliance on complex post-processing and strong prior knowledge. …”
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BFS: A blockchain-based financing scheme for logistics company in supply chain finance by Jia Fu, Bangcan Cao, Xiaoliang Wang, Pengjie Zeng, Wei Liang, Yuzhen Liu

“…On the other hand, the massive access to logistics companies’ business information can also lead to privacy leaks. At the same time, the transparency feature of blockchain is used to solve the financing dilemma of many industries in supply chain finance. …”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Abstract The detection of cracks in large structures is of critical importance, as such damage can result not only in significant financial costs but also pose serious risks to public safety. Many existing methods for crack detection rely on deep learning algorithms or traditional approaches that typically use image data. …”
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Pruritus in Uremic Patients: Approaches to Alleviating a Common Symptom in Chronic Kidney Disease by Ștefania Cîrstea, Olguța Anca Orzan, Diana Silvia Zilișteanu

“…Nonpharmacologic approaches are also evolving. Phototherapy, particularly UV-B therapy, modulates the immune response, reduces inflammation, and effectively alleviates itching in hemodialysis patients. …”
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Long duration multi-channel surface electromyographic signals during walking at natural pace: Data acquisition and analysis. by Francesco Di Nardo, Christian Morbidoni, Grazia Iadarola, Susanna Spinsante, Sandro Fioretti

“…Synchronized electrogoniometric and foot-floor-contact signals are also supplied to enable the spatial/temporal analysis of the sEMG signals. …”
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Leveraging artificial intelligence to assess the impact of COVID-19 on the teacher-student relationship in higher education. by Md Juwel Ahmed Sarker, Mahmudul Hasan, Alamgir Kabir, Abdullah Haque

“…We employed a subset of Artificial Intelligence (unsupervised machine learning) algorithms K-Modes clustering and Non-negative matrix factorization to cluster the data according to its internal structure. …”
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Explainable data mining model for hyperinsulinemia diagnostics by Nevena Rankovic, Dragica Rankovic, Mirjana Ivanovic, Igor Lukic

“…To address these challenges in the medical data analysis, we propose a model employing Functional Principal Component Analysis (FPCA), which also accounts for outliers that could otherwise lead to the inclusion of irrelevant features. …”
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A Topological Framework for Interactive Queries on 3D Models in the Web by Mauro Figueiredo, José I. Rodrigues, Ivo Silvestre, Cristina Veiga-Pires

“…However, there is no explicit topological information, which makes it difficult to design fast algorithms for applications that require adjacency and incidence data. …”
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Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China by Yiyang Li, Gang Yao, Shuangyi Li, Xiuru Dong

“…The estimation of soil organic matter (SOM) content is essential for understanding the chemical, physical, and biological functions of soil. It is also an important attribute reflecting the quality of black soil. …”
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Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…The results indicated significant improvements in energy, economic, spatial, and ecological dimensions, while also achieving quantifiable control over cultural expression. …”
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Data-driven decoding of quantum error correcting codes using graph neural networks by Moritz Lange, Pontus Havström, Basudha Srivastava, Isak Bengtsson, Valdemar Bergentall, Karl Hammar, Olivia Heuts, Evert van Nieuwenburg, Mats Granath

“…Accurate, maximum likelihood, decoders are computationally very expensive whereas decoders based on more efficient algorithms give sub-optimal performance. In addition, the accuracy will depend on the quality of models and estimates of error rates for idling qubits, gates, measurements, and resets, and will typically assume symmetric error channels. …”
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Hybrid MPPT Strategy: Optimizing SEIG Performance in Wind Energy Installation by Fadi Ouafia, Abbou Ahmed, Gaizen Soufiane

“…Our analysis indicates that the hybrid approach not only enhances tracking accuracy and convergence speed but also improves system stability compared to the standalone FF-ANN-based MPPT method. …”
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Generative AI as Third Agent: Large Language Models and the Transformation of the Clinician-Patient Relationship by Hugo de O Campos, Daniel Wolfe, Hongzhou Luan, Ida Sim

“…While affirming LLMs as a tool enabling the rise of the “AI patient,” we also explore concerns surrounding data privacy, algorithmic bias, moral injury, and the erosion of human connection. …”
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Axial-FNet: skin cancer image segmentation model based on fuzzy convolution combined with gated axial self-attention by JIANG Shu, CHEN Kun, DING Weiping, ZHOU Tianyi, ZHU Yue

“…The commonly used segmentation algorithms can't well balance the computational resource requirements of local information and global context information when performing diagnosis. …”
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Prediction of Corona-Virus Using Deep Learning by Laith Al-Ali

“…The data set is divided into 75% of the training data and 25% of the test data after applying deep learning algorithms. Python libraries such as pandas, NumPy, and matplotlib are also used in addition to sklearn and Keras. …”
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Long Short-Term Memory-Based Computerized Numerical Control Machining Center Failure Prediction Model by Jintak Choi, Zuobin Xiong, Kyungtae Kang

“…When rolling pins are machining with CNC equipment, a sensor system is installed to collect acoustic data, analyze failure patterns, and apply RUL prediction algorithms. The AI-based predictive maintenance system developed ensures the reliability and operational efficiency of CNC equipment, while also laying the foundation for a smart factory monitoring platform, thus enhancing competitiveness in intelligent manufacturing environments.…”
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A Systematic Review of CNN Architectures, Databases, Performance Metrics, and Applications in Face Recognition by Andisani Nemavhola, Colin Chibaya, Serestina Viriri

“…Overall, the findings emphasize the need for advanced algorithms capable of handling large-scale, real-world challenges while optimizing accuracy and computational efficiency in face recognition systems.…”
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Source reconstruction accuracy of MEG and EEG Bayesian inversion approaches. by Paolo Belardinelli, Erick Ortiz, Gareth Barnes, Uta Noppeney, Hubert Preissl

“…The localization performance was investigated as a function of (i) the number of sources (one vs. two vs. three), (ii) the signal to noise ratio (SNR; 5 levels) and (iii) the temporal correlation of source time courses (for the cases of two or three sources). We also tested whether the use of additional bilateral priors specifying source covariance for ARD and GS algorithms improved performance. …”
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COVID-19 Detection from Computed Tomography Images Using Slice Processing Techniques and a Modified Xception Classifier by Kenan Morani, Esra Kaya Ayana, Dimitrios Kollias, Devrim Unay

“…Results on the COV19-CT database showcased not only improvement from our previous solution and the baseline but also comparable performance to the highest-achieving methods on the same dataset. …”
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Using video for reconstruction in SfM. The Capo d’Omo Tower on Mount Argentario by Fabio Lanfranchi, Piero Barlozzini, Luca Martelli

“…The most advanced photo-modelling programs are now able to process video clips directly, automatically selecting the photos suitable for input in scale-invariant feature transform (SIFT) and speeded up robust features (SURF) algorithms, essential aspects of structure from motion (SfM). …”
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