alexandria engineering journal最新文献_第6页

Decoupled feature extraction and correspondence modeling for deformable medical image registration using large kernel attention 基于大核关注的可变形医学图像配准解耦特征提取与对应建模

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-24 DOI: 10.1016/j.aej.2025.12.033

Zhou Zhou , Chenglong Fu , Chuang Wang , Ping Zhu , Kaijian Xia , Pengjiang Qian

Medical image registration aims to align images acquired at different times, perspectives, or modalities. Traditional deep learning approaches typically combine moving and fixed images as joint inputs, limiting the model’s ability to independently process image features and achieve accurate voxel-level correspondences. This paper introduces a novel registration framework, DELCA-Net, which decouples feature extraction from correspondence modeling using a large kernel attention (LKA) mechanism. DELCA-Net utilizes a dual-stream shared encoder that separately processes moving and fixed images, capturing long-range semantic dependencies. Additionally, we propose a Cross-Resolution Attention Refinement Module (CARM) that enhances multi-scale spatial correspondences via a coarse-to-fine fusion strategy, improving anatomical feature alignment across resolutions. Comprehensive experiments conducted on the OASIS and IXI datasets demonstrate that our method consistently improves registration accuracy while offering better interpretability and computational efficiency. On the IXI dataset, our model achieves a 1.2% increase in the DICE coefficient while requiring only 1.9% of the parameters of TransMorph. Additionally, the implementation of our method is publicly available at https://github.com/windandink/DELCA-NET.

医学图像配准的目的是对齐在不同时间、视角或模式下获得的图像。传统的深度学习方法通常将运动和固定图像作为联合输入，限制了模型独立处理图像特征和实现精确体素级对应的能力。本文介绍了一种新的配准框架DELCA-Net，该框架利用大核注意（large kernel attention， LKA）机制将特征提取与对应建模解耦。DELCA-Net采用双流共享编码器，分别处理移动和固定图像，捕获远程语义依赖。此外，我们提出了一个跨分辨率注意力细化模块（CARM），该模块通过粗到细的融合策略增强了多尺度空间对应，改善了跨分辨率的解剖特征对齐。在OASIS和IXI数据集上进行的综合实验表明，该方法在提高配准精度的同时具有更好的可解释性和计算效率。在IXI数据集上，我们的模型实现了DICE系数增加1.2%，而只需要1.9%的TransMorph参数。此外，我们的方法的实现可以在https://github.com/windandink/DELCA-NET上公开获得。

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引用次数: 0

Precise tunnel lining crack detection using multimodal fusion transformer and metaheuristic-optimized ResNet-50 基于多模态融合变压器和元启发式优化的ResNet-50的隧道衬砌裂纹精确检测

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-24 DOI: 10.1016/j.aej.2025.12.022

Zhen Chen , Zhixi Shen

Automated crack detection in tunnel linings is critical for ensuring infrastructure safety and facilitating efficient long-term maintenance. Manual inspection methods are typically slow, labour-intensive, and inconsistent, highlighting the necessity for advanced automated solutions. This research presents a Mathematical Multimodal Fusion Transformer-Based Optimization (MMFTO) framework that integrates multiple tunnel-lining image modalities to enable robust crack identification. The framework utilizes an optimized multimodal fusion transformer encoder to extract and combine complementary features that are often missed by unimodal systems. Hyper-parameter tuning is conducted using an Improved Piranha Foraging Optimization Algorithm (IPFOA) algorithm, followed by feature refinement with a Modified Sunflower Optimization Algorithm (MSFOA). Final classification is performed by a DeepResNet-50 model. The proposed MMFTO–MSFO–DeepResNet50 system is evaluated on a newly curated multimodal tunnel-lining dataset and compared with existing deep-learning and unimodal approaches. The model achieves 95 % accuracy, 92 % precision, 92 % F1-score, 91 % recall, a mean average precision (mAP) of 94.7 %, and a mean intersection over union (mIoU) of 93.6 %. Further evaluation on Crack500, Tunnel200, and DeepCrack datasets demonstrates strong robustness and generalizability. These results indicate that the framework offers significant potential for real-world tunnel monitoring and intelligent infrastructure management.

隧道衬砌的自动裂缝检测对于确保基础设施安全和促进有效的长期维护至关重要。人工检查方法通常是缓慢的，劳动密集型的，并且不一致的，突出了先进的自动化解决方案的必要性。本研究提出了一种基于数学多模态融合变压器的优化（MMFTO）框架，该框架集成了多种隧道衬砌图像模式，以实现鲁棒的裂缝识别。该框架利用优化的多模态融合变压器编码器来提取和组合单模态系统经常错过的互补特征。使用改进的食人鱼觅食优化算法（IPFOA）进行超参数调优，然后使用改进的向日葵优化算法（MSFOA）进行特征细化。最终分类由DeepResNet-50模型进行。提出的MMFTO-MSFO-DeepResNet50系统在新编制的多模式隧道衬里数据集上进行了评估，并与现有的深度学习和单模态方法进行了比较。该模型的准确率为95 %，精密度为92 %，F1-score为92 %，召回率为91 %，平均平均精度（mAP）为94.7 %，平均交联（mIoU）为93.6 %。对Crack500、Tunnel200和DeepCrack数据集的进一步评估显示出较强的鲁棒性和泛化性。这些结果表明，该框架为现实世界的隧道监测和智能基础设施管理提供了巨大的潜力。

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引用次数: 0

Can Dengue be controlled? Assessing vaccination and insecticide strategies with optimal control 登革热能被控制吗？以最优控制评估疫苗接种和杀虫剂策略

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-23 DOI: 10.1016/j.aej.2025.12.039

Kamrunnesa Mayeda , Sadia Akter Lima , Amin Ullah , Md. Kamrujjaman

Dengue fever is an enormous global public health burden, with millions of cases reported annually. In this paper, we have introduced a mathematical model that is capable of describing the transmission of dengue with hospitalization and vaccination and characterizing the infection’s dynamics. We calculate the basic reproduction number,

0 < R_{0} < 1

, that indicates the die-out of this infection. Initially, the fundamental mathematical findings are illustrated. Further, we compare different population dynamics with vaccination and without vaccination, and the results are satisfying and can also control the infection. We examine diverse characteristics’ impact on distinct population dynamics. In addition, the functions that are in charge of controlling this infection are used to come up with the best control strategies, which gives us the best control of characterization. We solve the model of optimal control numerically and do the correlative study between the control strategies: prevention and insecticide, which are the strongest options to rid a community of this disease. The finding suggests that including hospitalization and vaccination in the transmission model and control strategies (prevention and insecticide) can drastically cut down the infection of dengue fever as well as stop it from further spreading in a community.

登革热是一个巨大的全球公共卫生负担，每年报告的病例达数百万例。在本文中，我们介绍了一个数学模型，能够描述登革热的传播与住院和疫苗接种和表征感染的动态。我们计算基本繁殖数0<；R0<1，这表明这种感染的死亡。首先，说明了基本的数学发现。此外，我们比较了接种疫苗和未接种疫苗的不同种群动态，结果令人满意，也可以控制感染。我们研究了不同特征对不同种群动态的影响。此外，控制这种感染的功能被用来提出最好的控制策略，这给了我们最好的特征控制。对最优控制模型进行了数值求解，并对预防和杀虫剂这两种控制策略之间的相关性进行了研究，这两种控制策略是消除该疾病的最强选择。这一发现表明，在传播模式和控制策略（预防和杀虫剂）中纳入住院和疫苗接种可以大大减少登革热的感染，并阻止其在社区中进一步传播。

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引用次数: 0

Corrigendum to "Provide personalized programming learning for individuals based on large language models'" [Alex. Eng. J., 132 (2025) 396–406] “基于大型语言模型为个人提供个性化编程学习”的勘误表[Alex]。Eng。J., 132 (2025) 396-406]

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-23 DOI: 10.1016/j.aej.2025.12.045

Chong Li , Xin Lee , Xiaojin Wu

引用次数: 0

Modeling predator-prey dynamics with stochastic differential equations: Patterns of collective hunting and nonlinear predation effects 用随机微分方程模拟捕食者-猎物动力学：集体狩猎模式和非线性捕食效应

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-22 DOI: 10.1016/j.aej.2025.12.038

Junyi Qi, Tôn Việt Tạ

We investigate predator–prey school interactions in aquatic environments using a stochastic differential equation (SDE)-based, particle-level model that incorporates attraction, repulsion, alignment, and environmental noise. Two predation strategies — center attack and nearest attack — are examined to assess their effects on prey survival, predator efficiency, and group dynamics. Simulations reveal diverse emergent behaviors such as prey dispersal and regrouping, oscillatory predation with collective defense, and predator encirclement. Results show that collective hunting enhances capture efficiency compared to solitary attacks, but benefits diminish beyond a critical predator group size due to intra-predator competition. This work provides new insights into cooperative predation and introduces a generalizable SDE framework for analyzing predator–prey interactions.

研究人员利用基于随机微分方程（SDE）的粒子级模型研究了水生环境中捕食者-猎物群体的相互作用，该模型包含了吸引力、排斥力、对齐和环境噪声。研究了两种捕食策略——中心攻击和最近攻击——以评估它们对猎物生存、捕食者效率和群体动力学的影响。模拟结果揭示了多种突发性行为，如猎物分散和重组，振荡捕食和集体防御，以及捕食者包围。结果表明，与单独攻击相比，集体狩猎提高了捕获效率，但由于捕食者之间的竞争，超过了关键的捕食者群体规模，收益就会减少。这项工作为合作捕食提供了新的见解，并为分析捕食者-猎物相互作用引入了一个可推广的SDE框架。

引用次数: 0

Experimental and analytical studies on the compressive behaviors of a 3D-printed sand mold-cast S-CN connector in modular steel buildings 3d打印砂铸模S-CN连接器在模块化钢结构中的抗压性能试验与分析研究

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-22 DOI: 10.1016/j.aej.2025.12.013

Tran-Van Han , Jeong MoonSook , YongNam Kim , Tra Ngoc Sanh , Nguyen Huu Cuong , Kihak Lee

Steel modular construction offers advantages in speed, cost, and sustainability, but its adoption is constrained by connection efficiency. This study introduces the Samsung Connection Node (S-CN), a novel cast-steel connector fabricated using 3D-printed sand molds. Full-scale tests on roof nodes, floor nodes, the connector, and a beam–column assembly under axial compression were conducted, supported by finite element (FE) and analytical studies. Roof nodes carried 10% higher loads than floor nodes, while connector strength was governed by tie plate deformation and local buckling. Beam restraint improved load utilization, producing higher uniformity of strain. Code-based predictions (AISC 360-16 EN 1993-1-1) provided conservative agreement with experiments and FE. A mechanics-based model clarified that rim bearing controls global capacity, while yield-line mechanisms explain local deformation. Parametric studies highlighted the strong influence of node thickness and adverse effects of large openings or excessive column height. Supplementary FE analyses under combined axial–moment loading indicated a stable numerical response of the connector and suggested robustness under service-level eccentricities. A nonlinear pushover analysis of a corner subassembly suggested a ductility ratio of 7.5 with drift ratios below the ASCE 7 and Eurocode 8 near-collapse limits in the numerical model; these seismic-related findings are preliminary and require future experimental validation.

钢模块结构在速度、成本和可持续性方面具有优势，但其采用受到连接效率的限制。本研究介绍了三星连接节点（S-CN），这是一种使用3d打印砂模制造的新型铸钢连接器。在有限元（FE）和分析研究的支持下，对屋顶节点、地板节点、连接器和轴向压缩下的梁柱组件进行了全尺寸测试。顶节点承受的荷载比底板节点高10%，接头强度受拉板变形和局部屈曲的影响。梁约束提高了载荷利用率，产生更高的均匀应变。基于代码的预测（AISC 360-16 EN 1993-1-1）与实验和有限元结果保守一致。基于力学的模型表明，轮辋轴承控制全局能力，而屈服线机制解释局部变形。参数研究强调了节点厚度的强烈影响和大开口或过高柱高的不利影响。在联合轴矩载荷下的补充有限元分析表明，连接器的数值响应稳定，并且在服务级偏心下具有鲁棒性。对角部组件的非线性推覆分析表明，其塑性比为7.5，漂移比低于ASCE 7和欧洲规范8的接近崩溃极限；这些与地震有关的发现是初步的，需要未来的实验验证。

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引用次数: 0

Design, simulation, and experimental validation of metamaterials with direction-dependent stiffness 具有方向相关刚度的超材料的设计、模拟和实验验证

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-20 DOI: 10.1016/j.aej.2025.12.031

Hossein Rahimi , Mahdi Khajepour , Davood Rahmatabadi , Ghader Faraji , Mostafa Baghani , Daniel George , Majid Baniassadi

Mechanical metamaterials derive their functionality from geometry rather than composition, yet achieving experimentally validated three-dimensional direction-dependent stiffness (DDS) has remained challenging. This work introduces a 3D metamaterial unit cell with strong, tunable DDS, developed through a heuristic, gradient-free optimization framework that iteratively generated and refined geometries using finite element analysis. The final design features asymmetric internal struts and orientation-specific contact surfaces that activate bending- or stretching-dominated modes depending on loading direction. The unit cell and corresponding lattices were fabricated using high-resolution digital light processing (DLP) additive manufacturing and tested under compression along all three orthogonal axes. Simulations and experiments show excellent agreement (<1 % deviation), confirming distinct mechanical responses in the X, Y, and Z directions. The structure exhibits a stiffness increase above 350 % across deformation regions and up to 80 % contrast between its stiffest and most compliant orientations, while maintaining smooth force–displacement behavior with negligible stress concentrations. It also demonstrates substantial direction-dependent energy absorption, reaching several hundred joules in the stiffest orientation. These results establish a practical and manufacturable pathway toward architected materials with true 3D DDS, offering strong potential for exoskeletons, crash-protection systems, biomedical implants, and seismic-resistant components.

机械超材料的功能来源于几何形状，而不是成分，但实现实验验证的三维方向相关刚度（DDS）仍然具有挑战性。这项工作介绍了一种具有强大可调DDS的3D超材料单元格，该单元格通过启发式、无梯度优化框架开发，该框架使用有限元分析迭代生成和改进几何形状。最终设计的特点是不对称的内部支柱和方向特定的接触面，根据加载方向激活弯曲或拉伸主导模式。采用高分辨率数字光处理（DLP）增材制造技术制作了单元胞和相应的晶格，并沿着所有三个正交轴进行了压缩测试。模拟和实验显示了极好的一致性（<；1 %偏差），证实了X， Y和Z方向上不同的机械响应。结构在变形区域的刚度增加超过350 %，在其最刚度和最柔顺方向之间的对比高达80 %，同时保持平滑的力-位移行为，应力集中可以忽略不计。它还显示了大量的方向依赖的能量吸收，在最硬的方向上达到几百焦耳。这些结果为具有真正3D DDS的建筑材料建立了实用和可制造的途径，为外骨骼，碰撞保护系统，生物医学植入物和抗震组件提供了强大的潜力。

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引用次数: 0

Assessment of groundwater quantity and quality indexes and WQI determination for drinking and agricultural uses: Alborz Plain, Iran case study 用于饮用和农业用途的地下水数量和质量指标评价及WQI的确定：伊朗Alborz平原案例研究

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-19 DOI: 10.1016/j.aej.2025.12.025

Mehdi Hedayatpour , Hamidreza Rabieifar , Hossein Hassanpour Darvishi , Reza Shirinabadi , Saeid Farokhizadeh

This study evaluates groundwater quantity and quality variations in Alborz Plain and assesses suitability for drinking and agriculture using the Water Quality Index (WQI). Data from 19 aquifers (2002–2023) were analyzed for key parameters: K⁺, Na⁺, Mg²⁺, Ca²⁺, SO₄²⁻, Cl⁻, HCO₃⁻, NO₃⁻, pH, EC, and TDS. Piper, Scholler, and Wilcox diagrams were prepared using Aq.QA and MATLAB to identify dominant facies and evaluate agricultural and drinking suitability. WQI results indicate “very good” quality in northwest and central regions, declining to “good” in east and improving in southeast. Dominant facies include Ca-HCO₃ or Mg-HCO₃ in northwest, center, and southeast, and Na-HCO₃ in east, with three aquifers exhibiting Na-SO₄, Na-Cl, and Ca-SO₄ facies. W1 and W3 aquifers are suitable for drinking despite high EC but show agricultural limitations in salt-sensitive areas. Long-term quality trends were assessed using Mann-Kendall test and Sen’s slope, while PCA and K-means clustering identified seven stable aquifer groups. SVR and Random Forest models accurately predicted TDS trends. Salinity is mainly influenced by regional geology, including evaporitic and dolomitic rocks, rather than proximity to sea. This integrated approach provides a practical framework for understanding groundwater dynamics and supporting sustainable management at regional and national levels.

本研究利用水质指数（WQI）评价了阿尔博斯平原地下水的数量和质量变化，并对饮用和农业适宜性进行了评价。对来自19个含水层（2002-2023年）的数据进行了关键参数分析：K⁺、Na⁺、Mg⁺、Ca⁺、SO₄²⁻、Cl⁻、HCO₃⁻、NO₃⁻、pH、EC和TDS。利用Aq.QA和MATLAB编制Piper、Scholler和Wilcox图，确定优势相，评价农业和饮用适宜性。WQI结果显示，西北和中部地区为“非常好”，东部地区为“好”，东南部地区为“好”。主要相为西北部、中部和东南部的Ca-HCO₃或Mg-HCO₃，东部的Na-HCO₃，3个含水层表现为Na-SO₄、Na-Cl和Ca-SO₄相。W1和W3含水层适合饮用，尽管高EC，但在盐敏感地区显示出农业限制。采用Mann-Kendall检验和Sen’s slope对含水层的长期质量趋势进行了评价，而PCA和K-means聚类则确定了7个稳定的含水层组。SVR和随机森林模型准确地预测了TDS的趋势。盐度主要受区域地质影响，包括蒸发岩和白云岩，而不是靠近海洋。这种综合方法为了解地下水动态和支持区域和国家一级的可持续管理提供了一个实用框架。

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引用次数: 0

Quantum-inspired deep learning optimisation for real-time student engagement analysis in virtual classrooms 量子启发的深度学习优化，用于虚拟教室中的实时学生参与分析

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-19 DOI: 10.1016/j.aej.2025.12.019

Hanan T. Halawani , Shuhrah Alghamdi , Fahad Ali Aloufi , Maryam Alsolami , Abdulellah Alsulaimani , Hassan M. Aljohani

Quantum computing (QC) employs quantum-mechanical principles such as superposition and entanglement to solve specific problems far more efficiently than classical computers. E-learning is the only option for students and teachers during the pandemic. Conversely, it is challenging for an instructor to observe every student’s engagement while educating online. Students are distracted during such activities. The teachers want to identify their students' states, whether they are concentrated or concerned with teaching. Hence, from a teacher’s viewpoint, it is significant to assess students' levels of engagement to understand their actual reactions and take the necessary steps to involve students and help them achieve goals, machine learning (ML) and deep learning (DL) is deployed for predictive analytics of a student’s performance and engagement depending upon interactions, contribution in class, etc. In this paper, the Deep Learning-Driven Quantum Inspired Moth Flame Optimizer for Real-Time Student Engagement Analysis (DLQIMFO-RSEA) method is proposed. The DLQIMFO-RSEA method aims to categorise student engagement in online classes. To accomplish this, the DLQIMFO-RSEA method uses the YOLOv5 object detection model with backbones SPPF, CBS, and CSPI-X. Next, the image pre-processing stage employs the Wiener filter (WF) to remove the noise. For feature extraction, the InceptionResNetV2 technique is used. Furthermore, a stacked autoencoder (SAE) is applied for detection. At last, the parameter tuning process is performed by the quantum-inspired moth flame optimiser (QIMFO) model to improve the classification performance of the SAE model. The comparison analysis of the DLQIMFO-RSEA approach showed superior accuracy of 94.34 % compared to other models on the student engagement dataset.

量子计算（QC）利用量子力学原理，如叠加和纠缠来解决特定问题，比经典计算机更有效。电子学习是大流行期间学生和教师的唯一选择。相反，对于教师来说，在线教学时观察每个学生的参与度是一项挑战。学生们在这样的活动中会分心。教师想要识别学生的状态，无论他们是专注于教学还是专注于教学。因此，从教师的角度来看，评估学生的参与水平以了解他们的实际反应并采取必要的步骤让学生参与并帮助他们实现目标是很重要的，机器学习（ML）和深度学习（DL）被用于根据互动、课堂贡献等对学生的表现和参与进行预测分析。本文提出了一种深度学习驱动的量子启发飞蛾火焰优化器实时学生参与分析（DLQIMFO-RSEA）方法。DLQIMFO-RSEA方法旨在对学生在在线课程中的参与度进行分类。为了实现这一点，DLQIMFO-RSEA方法使用YOLOv5目标检测模型，该模型具有骨干SPPF、CBS和CSPI-X。接下来，图像预处理阶段采用维纳滤波器（WF）去除噪声。对于特征提取，使用了InceptionResNetV2技术。此外，采用堆叠自编码器（SAE）进行检测。最后，采用量子启发飞蛾火焰优化器（QIMFO）模型进行参数整定，提高SAE模型的分类性能。DLQIMFO-RSEA方法的对比分析显示，与学生参与数据集上的其他模型相比，DLQIMFO-RSEA方法的准确率为94.34 %。

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引用次数: 0

NumLin-Mamba-YOLO: A YOLO object detection algorithm based on Mamba architecture and multi-scale feature optimization NumLin-Mamba-YOLO：一种基于Mamba架构和多尺度特征优化的YOLO目标检测算法

IF 6.8 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2025-12-19 DOI: 10.1016/j.aej.2025.11.011

Qinnan Luo

Object detection in complex scenes, especially for small object detection, faces significant challenges in real-time performance and multi-scale accuracy. This study proposes an improved algorithm, NumLin-Mamba-YOLO, designed to enhance detection performance by integrating numerical linear algebra techniques with the Mamba module. The aim of this research is to optimize detection performance through a series of multi-module innovations. The algorithm utilizes Singular Value Decomposition (SVD) and Principal Component Analysis (PCA) in the backbone network for feature dimensionality reduction, denoising, and redundancy elimination, thereby enhancing feature discriminability. It also leverages the linear time complexity advantage of Mamba’s State Space Model (SSM) to model global dependencies. An enhanced feature fusion network improves cross-scale feature correlation, while a decoupled attention detection head is designed to independently optimize classification and regression tasks, improving sensitivity to small objects and local details. Experiments on the Visdrone and PASCAL VOC datasets demonstrate that the algorithm achieves substantial improvements in both detection accuracy and inference efficiency in complex and general scenes, with particular strength in small object detection. The model effectively controls parameters and computational load, providing an efficient solution for real-world object detection applications in intelligent monitoring and autonomous driving.

复杂场景下的目标检测，特别是小目标检测，在实时性和多尺度精度方面面临着巨大的挑战。本研究提出了一种改进算法NumLin-Mamba-YOLO，旨在通过将数值线性代数技术与Mamba模块相结合来提高检测性能。本研究的目的是通过一系列多模块创新来优化检测性能。该算法利用主干网络中的奇异值分解（SVD）和主成分分析（PCA）对特征进行降维、去噪和冗余消除，从而增强特征的可分辨性。它还利用了Mamba的状态空间模型（SSM）的线性时间复杂度优势来建模全局依赖关系。增强的特征融合网络提高了跨尺度特征相关性，同时设计了解耦的注意检测头，独立优化分类和回归任务，提高了对小目标和局部细节的灵敏度。在Visdrone和PASCAL VOC数据集上的实验表明，该算法在复杂场景和一般场景下的检测精度和推理效率都有了很大的提高，在小目标检测方面尤为突出。该模型有效地控制了参数和计算负荷，为智能监控和自动驾驶中的现实世界目标检测应用提供了高效的解决方案。

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引用次数: 0