Real-time damage detection of bridges using adaptive time-frequency analysis and ANN by V. Ahmadian, S. B. Beheshti Aval, E. Darvishan

“…First, three adaptive signal processing techniques including Empirical Mode Decomposition (EMD), Local Mean Decomposition (LMD) and Hilbert Vibration Decomposition (HVD) are compared. …”
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MSDNet: A Multi-Scale Feature Representation Network Model for Tunnel Bolt Detection by Xiufeng Wu, Xueli Li, Guangxing Cao, Chao Guo, Wei Chang, Zhao Wang, Shuliang Liu

“…However, identifying a large number of corroded bolts presents challenges, particularly due to interference from complex background noise and the inherent limitations of CNNs in extracting local features. To address these issues, we introduces a novel multi-scale feature extraction detection network (MSDNet) designed to improve tunnel bolt maintenance by reducing false positives and missed detections. …”
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Detecting and Identifying Industrial Gases by a Method Based on Olfactory Machine at Different Concentrations by Yunlong Sun, Dehan Luo, Hui Li, Chuchu Zhu, Ou Xu, Hamid Gholam Hosseini

“…Gas sensors have been widely reported for industrial gas detection and monitoring. However, the rapid detection and identification of industrial gases are still a challenge. …”
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Low resolution remote sensing object detection with fine grained enhancement and swin transformer by Zhijing Xu, Xin Wang, Kan Huang, Ren Chen

“…Second, we develop the Swin Transformer-based Progressive Aggregation Network (STPANet), which integrates Swin Transformer Blocks into the C3CST module to achieve superior multi-scale feature fusion while simultaneously capturing global contextual information and local spatial details. Finally, we incorporate the Shape-IoU loss function to optimize bounding box regression, significantly improving small target detection accuracy while maintaining computational efficiency. …”
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Face Forgery Detection with Long-Range Noise Features and Multilevel Frequency-Aware Clues by Yi Zhao, Xin Jin, Song Gao, Liwen Wu, Shaowen Yao, Qian Jiang

“…Consequently, face forgery detection has emerged as a prominent topic of research to prevent technology abuse. …”
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An Explainable LSTM-Based Intrusion Detection System Optimized by Firefly Algorithm for IoT Networks by Taiwo Blessing Ogunseyi, Gogulakrishan Thiyagarajan

“…To explain the proposed model’s predictions and increase trust in its outcomes, we applied two explainable artificial intelligence (XAI) tools: Local Interpretable Model-agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP), providing valuable insights into the model’s behavior.…”
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Molecular Detection and Characterization of New Emerging Viruses by PCR Analysis in Hatay and Tekirdag Vineyards by Hamide Deniz Kocabağ, Kadriye Çağlayan, Mona Gazel

“…Among the tested samples GPGV and GSyV-1 were detected in both local and imported cultivars by the infection rate of 43.62 % and 1.04% in Tekirdağ , respectively. …”
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DADNet: text detection of arbitrary shapes from drone perspective based on boundary adaptation by Jun Liu, Jianxun Zhang, Ting Tang, Shengyuan Wu

“…Abstract The rapid development of drone technology has made drones one of the essential tools for acquiring aerial information. The detection and localization of text information through drones greatly enhance their understanding of the environment, enabling tasks of significant importance such as community commercial planning and autonomous navigation in intelligent environments. …”
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Truck Lifting Accident Detection Method Based on Improved PointNet++ for Container Terminals by Yang Shen, Xintai Man, Jiaqi Wang, Yujie Zhang, Chao Mi

“…This method uses multi-line LiDAR to collect point cloud data from operational lanes in real time and enhances the PointNet++ model by integrating a multi-layer perceptron (MLP) and a mixed attention mechanism (MAM), optimizing the model’s ability to extract local and global features. This results in high-precision semantic segmentation and accident detection of critical structural point clouds, such as containers, truck chassis, and wheels. …”
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YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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Anchor point based image registration for absolute scale topographic structure detection in microscopy by Zhuo Diao, Zijie Meng, Fengxuan Li, Linfeng Hou, Hayato Yamashita, Tetsuya Tohei, Masayuki Abe, Akira Sakai

“…Additionally, the method provides valuable information from the registered anchor points, allowing for the precise localization of local objects in the structure. We demonstrate this technique across various microscopy scenarios at different scales and evaluate its precision against a keypoint detection AI approach from our previous research, which promises its enhancement in microscopy data analysis and automation.…”
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Federal Deep Learning Approach of Intrusion Detection System for In-Vehicle Communication Network Security by In-Seop Na, Anandakumar Haldorai, Nithesh Naik

“…Experimental results show that the proposed technique can effectively detect attacks in real-time on the bus, with a much higher detection ratio. …”
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Dual-Stream Global Relationship Learning for Oriented Object Detection in Remote Sensing Images by Peng Sun, Yongbin Zheng, Wanying Xu, Jiansong Yang

“…Oriented object detection has attained remarkable progress in addressing the challenges associated with rotating invariant feature extraction. …”
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Oral cancer detection via Vanilla CNN optimized by improved artificial protozoa optimizer by Yulong Chai, Xiuqing Chai, Lan Zhang, Gang Ye, Fatima Rashid Sheykhahmad

“…Due to its effectiveness in search space exploration while avoiding local optimal points, the IAPO algorithm is chosen to optimize the convolutional neural network. …”
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Ocean color anomaly detection to estimate surface Calanus finmarchicus concentration in the Gulf of Maine by Rebekah Shunmugapandi, Cait L. McCarry, David McKee, David McKee, Catherine Mitchell

“…This study investigated the application of ocean color remote sensing to detect the surface population levels of C. finmarchicus in the GoM. …”
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A Cross-Fusion Network for Salient Object Detection in Optical Remote Sensing Images by Weining Zhai, Panpan Zheng, Liejun Wang

“…The existed RSI-SOD models, however, face a challenge on how to balance global context and local detailed information efficiently due to varying object scales and cluttered backgrounds in RSIs. …”
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Research on a Bone Stick Fragment Stitching Method Based on Improved Corner Detection by Jiahuan Liu, Huiqin Wang, Rui Liu, Ke Wang, Zhan Wang, Ting Wang

“…Then, the broken edge features are enhanced by combining multi-scale and multi-stage corner detection, as well as a double screening mechanism of local template and corner density analysis. …”
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Co-occurrence patterns based fruit quality detection for hierarchical fruit image annotation by Sangita B. Nemade, Shefali P. Sonavane

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A Clustering Algorithm Based on the Detection of Density Peaks and the Interaction Degree Between Clusters by Yangming Liu, Jiaman Ding, Hongbin Wang, Yi Du

“…In order to cope with data with an irregular shape and uneven density, this paper proposes a two-phase clustering algorithm based on detecting the peaks of dimensional density and the degree of interaction between clusters (CPDD-ID). …”
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Walnut Surface Defect Classification and Detection Model Based on Enhanced YOLO11n by Xinyi Ma, Zhongjia Hao, Shuangyin Liu, Jingbin Li

“…Finally, the EIoU loss function is adopted to enhance the model’s localization capability for irregularly shaped defects and reduce false detection rates by improving the scale sensitivity of bounding box regression. …”
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