An Interpretable Siamese Attention Res-CNN for Fingerprint Spoofing Detection by Chengsheng Yuan, Zhenyu Xu, Xinting Li, Zhili Zhou, Junhao Huang, Ping Guo

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RTDU: Interpretable Region-Aware Transformer-Based Deep Unfolding Network for Pan-Sharpening by Shuo Wang, Genji Yuan, Jinjiang Li

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Lightweight YOLOv8s-Based Strawberry Plug Seedling Grading Detection and Localization via Channel Pruning by CHEN Junlin, ZHAO Peng, CAO Xianlin, NING Jifeng, YANG Shuqin

“…[Results and Discussions]The pruning process inevitably resulted in the loss of some parameters that were originally beneficial for feature representation and model generalization. …”
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Reduced Noise Effect in Nonlinear Model Estimation Using Multiscale Representation by Mohamed N. Nounou, Hazem N. Nounou

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Enhancing Digital Twin Fidelity Through Low-Discrepancy Sequence and Hilbert Curve-Driven Point Cloud Down-Sampling by Yuening Ma, Liang Guo, Min Li

“…We propose a novel down-sampling approach that combines Low-Discrepancy Sequences (LDS) with Hilbert curve ordering to create a method that preserves both global distribution characteristics and local geometric features. Unlike traditional methods that impose uniform density or rely on computationally intensive feature detection, our LDS-Hilbert approach leverages the complementary mathematical properties of Low-Discrepancy Sequences and space-filling curves to achieve balanced sampling that respects the original density distribution while ensuring comprehensive coverage. …”
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Infrared Small-Target Detection via Improved Density Peak Clustering and Gray-Level Contribution by Lang Wu, Fan Fan, Jun Huang, Guoqiang Xiao

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Detection of egg appreance based on Fasternet and YOLOv5 model by WEI Jingxin, CHEN Zhongju, XU Haoran

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Surface morphology segmentation and evaluation of diamond lapping pad based on improved Mask R-CNN by Wenlong SUO, Yanfen LIN, Congfu FANG

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AI bot to detect fake COVID‐19 vaccine certificate by Muhammad Arif, Shermin Shamsudheen, F Ajesh, Guojun Wang, Jianer Chen

“…So, to avoid this huge problem, this paper focuses on detecting fake vaccine certificates using a bot powered by Artificial Intelligence and neurologically powered by Deep Learning in which the following are the stages: a) Data Collection, b) Preprocessing to remove noise from the data, and convert to grayscale and normalised, c) Error level analysis, d) Texture‐based feature extraction for extracting logo, symbol and for the signature we extract Crest‐Trough parameter, and e) Classification using DenseNet201 and thereby giving the results as fake/real certificate. …”
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Learning Interactions between Rydberg Atoms by Olivier Simard, Anna Dawid, Joseph Tindall, Michel Ferrero, Anirvan M. Sengupta, Antoine Georges

“…Quantum simulators have the potential to solve quantum many-body problems that are beyond the reach of classical computers, especially when they feature long-range entanglement. …”
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Innovative and sustainable solar cells based on abundant elements on the Earth crust by Pasini Stefano, Foti Gianluca, Parisini Antonella, Spoltore Donato, Fornari Roberto, Bosio Alessio, Marchionna Stefano

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Link-State-Aware Proactive Data Delivery in Integrated Satellite–Terrestrial Networks for Multi-Modal Remote Sensing by Ranshu Peng, Chunjiang Bian, Shi Chen, Min Wu

“…This paper seeks to address the limitations of conventional remote sensing data dissemination algorithms, particularly their inability to model fine-grained multi-modal heterogeneous feature correlations and adapt to dynamic network topologies under resource constraints. …”
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Automated Early-Stage Glaucoma Detection Using a Robust Concatenated AI Model by Wheyming Song, Ing-Chou Lai

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A Low Complexity Algorithm for 3D-HEVC Depth Map Intra Coding Based on MAD and ResNet by Erlin Tian, Jiabao Zhang, Qiuwen Zhang

“…This model effectively integrates both local and global features to generate partitioning predictions at various depths, while incorporating the quantization parameter (QP) into the input to enhance prediction accuracy. …”
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YOLO-Ginseng: a detection method for ginseng fruit in natural agricultural environment by Zhedong Xie, Zhuang Yang, Chao Li, Zhen Zhang, Jiazhuo Jiang, Hongyu Guo

“…The compressed model exhibits reductions of 76.4%, 79.3%, and 74.2% in terms of model weight size, parameter count, and computational load, respectively.DiscussionCompared to other models, YOLO-Ginseng demonstrates superior overall detection performance. …”
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On the Model Checking Problem for Some Extension of CTL* by Anton Romanovich Gnatenko, Vladimir Anatolyevich Zakharov

“…To provide temporal logics with the ability to define properties of transformations that characterize the behavior ofreactive systems, we introduced new extensions ofthese logics, which have two distinctive features: 1) temporal operators are parameterized, and languages in the input alphabet oftransducers are used as parameters; 2) languages in the output alphabet oftransducers are used as basic predicates. …”
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Representation Learning of Multi-Spectral Earth Observation Time Series and Evaluation for Crop Type Classification by Andrea González-Ramírez, Clement Atzberger, Deni Torres-Roman, Josué López

“…Here, we propose a conceptually and computationally simple representation learning (RL) approach based on autoencoders (AEs) to generate discriminative features for crop type classification. …”
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Space Precession Target Classification Based on Radar High-Resolution Range Profiles by Yizhe Wang, Cunqian Feng, Yongshun Zhang, Sisan He

“…Effective classification of space targets is of great significance for further micromotion parameter extraction and identification. Feature extraction is a key step during the classification process, largely influencing the final classification performance. …”
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Deep Learning-Augmented Evolutionary Strategies for Intelligent Global Optimization by Absalom El-Shamir Ezugwu, Olaide Nathaniel Oyelade, Jeffrey Ovre Agushaka, Apu Kumar Saha

“…Additionally, SIRO was tested on real-world optimization problems, including mechanical engineering design, hyperparameter tuning, and feature selection for medical image classification. …”
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Climate Change Risk, Performance, and Value Added in Agricultural Sector by Ramin Amani, Zanko Ghorbani, Zana Mozaffari

“…The unique feature of this method is that it introduces a penalty term in the minimization to address the computational problem of a set of parameters; The parameters are calculated as follows: min(α.β)Σk=1KΣt=1TΣi=1N wkρτkyit-αi-xitTβτk+λΣiNαi                              (6) In equation (6), i represents the number of countries (N), T represents the index for the number of observations of each country, K represents the quantile index, x is the matrix of explanatory variables, and ρτk is the quantile loss function. …”
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