Multi-Level Intertemporal Attention-Guided Network for Change Detection in Remote Sensing Images by Shuo Liu, Qinyu Zhang, Yuhang Zhang, Xiaochen Niu, Wuxia Zhang, Fei Xie

“…These methods focus on regions of interest, improving detection accuracy and efficiency. However, external factors can introduce many pseudo-changes, presenting significant challenges for CD. …”
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An adaptive neuro-fuzzy inference scheme for defect detection and classification of solar PV cells by Ranganai Tawanda Moyo, Mendon Dewa, Héctor Felipe Mateo Romero, Victor Alonso Gómez, Jose Ignacio Morales Aragonés, Luis Hernández-Callejo

“…Traditional defect detection and classification methods often face challenges in providing precise and adaptable solutions to this complex problem. …”
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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

“…Abstract Object detection in remote sensing images is a highly complex and challenging task. …”
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YOLOv8n-SMMP: A Lightweight YOLO Forest Fire Detection Model by Nianzu Zhou, Demin Gao, Zhengli Zhu

“…Global warming has driven a marked increase in forest fire occurrences, underscoring the critical need for timely and accurate detection to mitigate fire-related losses. Existing forest fire detection algorithms face limitations in capturing flame and smoke features in complex natural environments, coupled with high computational complexity and inadequate lightweight design for practical deployment. …”
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RS-DETR: An Improved Remote Sensing Object Detection Model Based on RT-DETR by Hao Zhang, Zheng Ma, Xiang Li

“…Recently, deep-learning-based object detection has made significant progress. However, due to large variations in target scale, the predominance of small targets, and complex backgrounds in remote sensing imagery, remote sensing object detection still faces challenges, including low detection accuracy, poor real-time performance, high missed detection rates, and high false detection rates in practical applications. …”
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A lightweight fabric defect detection with parallel dilated convolution and dual attention mechanism by Zheqing Zhang, Kezhong Lu, Gaoming Yang

“…To increase detection efficiency, a variety of automatic fabric defect detections have been developed. …”
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Fibromyalgia Detection and Diagnosis: A Systematic Review of Data-Driven Approaches and Clinical Implications by Anirudh Atmakuru, Subrata Chakraborty, Massimo Salvi, Oliver Faust, Prabal Datta Barua, Makiko Kobayashi, Ru San Tan, Filippo Molinari, Abdul Hafeez-Baig, U. Rajendra Acharya

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Toward Model-Independent Separative Training for Deep Hyperspectral Anomaly Detection With Mask Guidance by Xi Su, Xiangfei Shen, Haijun Liu, Lihui Chen, Gemine Vivone, Xichuan Zhou

“…Hyperspectral anomaly detection (HAD) aims to recognize a minority of anomalies that are spectrally different from their surrounding background without prior knowledge. …”
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Oriented SAR Ship Detection Based on Edge Deformable Convolution and Point Set Representation by Tianyue Guan, Sheng Chang, Yunkai Deng, Fengli Xue, Chunle Wang, Xiaoxue Jia

“…Although extensive research has been conducted in this field, the interference of speckle noise in SAR images and the potential discontinuity of target contours continue to pose challenges for the accurate detection of multi-directional ships in complex scenes. …”
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Optimized Flexible Microheater With Integrated Electrodes and Microchannel for On-Chip Bacterial Incubation and Electrochemical Detection by Sonal Fande, Khairunnisa Amreen, D. Sriram, Sanket Goel

“…The fabricated microheater serves a multifaceted purpose, allowing for efficient growth conditions for culturing bacteria, their on-site quantification, and antibiotic susceptibility testing. …”
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Detection of Citrus Huanglongbing in Natural Field Conditions Using an Enhanced YOLO11 Framework by Liang Cao, Wei Xiao, Zeng Hu, Xiangli Li, Zhongzhen Wu

“…We constructed a multi-symptom HLB leaf dataset (MS-HLBD) containing 9219 annotated images across five classes: Healthy (1862), HLB blotchy mottling (2040), HLB Zinc deficiency (1988), HLB yellowing (1768), and Canker (1561), collected under diverse field conditions. To improve detection performance, the DCH-YOLO11 framework incorporates three novel modules: the C3k2 Dynamic Feature Fusion (C3k2_DFF) module, which enhances early and subtle lesion detection through dynamic feature fusion; the C2PSA Context Anchor Attention (C2PSA_CAA) module, which leverages context anchor attention to strengthen feature extraction in complex vein regions; and the High-efficiency Dynamic Feature Pyramid Network (HDFPN) module, which optimizes multi-scale feature interaction to boost detection accuracy across different object sizes. …”
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Flexible Screen‐Printed Electrochemical Sensor for Alkaline Phosphatase Detection in Biofluids for Biomedical Applications by Panagiota M. Kalligosfyri, Antonella Miglione, Alessia Esposito, Raghad Alhardan, Gabriella Iula, Iclal Atay, Ibrahim A. Darwish, Sevinc Kurbanoglu, Stefano Cinti

“…Conventional methods for ALP detection often require complex assay principles, extensive sample pretreatment, and trained personnel. …”
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YOLO-PWSL-Enhanced Robotic Fish: An Integrated Object Detection System for Underwater Monitoring by Lingrui Lei, Ying Tang, Weidong Zhang, Quan Tang, Haichi Hao

“…In fact, we designed a multilevel attention fusion block (LGFB) that enhances perception in complex scenarios, to optimize the accuracy of the detected frames, the Wise-ShapeIoU loss function was used, and in order to reduce the parameters and FLOPs of the model, a lightweight convolution method called PConv was introduced. …”
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A Lightweight Model for Small-Target Pig Eye Detection in Automated Estrus Recognition by Min Zhao, Yongpeng Duan, Tian Gao, Xue Gao, Guangying Hu, Riliang Cao, Zhenyu Liu

“…The MSCA module enhances small-object detection efficiency, while the PPA and GAM modules improve feature extraction capabilities. …”
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FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…RGB-IR object detection provides a promising solution for complex scenarios, such as remote sensing and low-light environments, by leveraging the complementary strengths of visible and infrared modalities. …”
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Hierarchical Feature Fusion and Enhanced Attention Mechanism for Robust GAN-Generated Image Detection by Weinan Zhang, Sanshuai Cui, Qi Zhang, Biwei Chen, Hui Zeng, Qi Zhong

“…Meanwhile, the AEM enhances the network’s ability to capture subtle forgery traces by incorporating attention mechanisms and filtering techniques, significantly boosting the model’s efficiency in processing complex information. The experimental results demonstrate that the proposed method achieves significant improvements across all evaluation metrics. …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…This study investigates the application effectiveness of deep learning-based object detection technology in forest fire smoke recognition by using the YOLOv11x algorithm to develop an efficient fire detection model. …”
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FEMNet: A Feature-Enriched Mamba Network for Cloud Detection in Remote Sensing Imagery by Weixing Liu, Bin Luo, Jun Liu, Han Nie, Xin Su

“…Accurate and efficient cloud detection is critical for maintaining the usability of optical remote sensing imagery, particularly in large-scale Earth observation systems. …”
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A Lightweight Pavement Defect Detection Algorithm Integrating Perception Enhancement and Feature Optimization by Xiang Zhang, Xiaopeng Wang, Zhuorang Yang

“…To address the current issue of large computations and the difficulty in balancing model complexity and detection accuracy in pavement defect detection models, a lightweight pavement defect detection algorithm, PGS-YOLO, is proposed based on YOLOv8, which integrates perception enhancement and feature optimization. …”
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TinyML-enabled fuzzy logic for enhanced road anomaly detection in remote sensing by Amna Khatoon, Weixing Wang, Mengfei Wang, Limin Li, Asad Ullah

“…Abstract Advanced techniques for detecting and classifying road anomalies are crucial due to road networks’ rapid expansion and increasing complexity. …”
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