Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction Using Biologically Inspired BWT and SVM by Nilesh Bhaskarrao Bahadure, Arun Kumar Ray, Har Pal Thethi

“…In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated Berkeley wavelet transformation (BWT) based brain tumor segmentation. …”
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Dynamic Wireless Power Transfer System for Indoor AGV With a Distance-Measurement-Based Position Detection Technique by Deniss Stepins, Janis Zakis, Aleksandrs Sokolovs, Oleksandr Husev, Ryszard Strzelecki, Rik W. de Doncker

“…However, the cost and level of complexity of the position detection system are moderately lower and the proposed position detection system is immune to optical radiation and magnetic fields. …”
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An intelligent method for detection of small target fungal wheat spores based on an improved YOLOv5 with microscopic images by Zhizhou Ren, Kun Liang, Yingqi Zhang, Jinpeng Song, Xiaoxiao Wu, Chi Zhang, Xiuming Mei, Yi Zhang, Xin Liu

“…Traditional detection methods are time-consuming and labor-intensive, and difficult to detect small target spores in complex environments. …”
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A Deep Learning-Based Approach for the Detection of Various Internet of Things Intrusion Attacks Through Optical Networks by Nouman Imtiaz, Abdul Wahid, Syed Zain Ul Abideen, Mian Muhammad Kamal, Nabila Sehito, Salahuddin Khan, Bal S. Virdee, Lida Kouhalvandi, Mohammad Alibakhshikenari

“…Furthermore, the model’s architecture leverages the high-speed, low-latency characteristics of optical networks, ensuring the efficient processing of large-scale IoT data streams and supporting real-time detection in diverse IoT ecosystems. …”
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Scalable Detection of Underground Water Leaks in Dense Urban Environments Using L-Band SAR and Machine Learning by E. Ali, E. Ali, L. Xie, A. Sani-Mohammed, W. Xu, T. Zayed

“…Underground water leaks in urban networks result in significant resource loss, infrastructure degradation, and environmental damage—challenges that are particularly acute in high-density cities like Hong Kong, where aging and complex infrastructure complicates detection. Traditional methods such as acoustic sensing and manual inspections often fall short in efficiency and scalability. …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…To overcome the drawbacks of manual defect detection and the challenges of traditional visual inspection algorithms, such as high missed detection rates, slow detection speeds, and difficulties in deployment on embedded devices for detecting subtle wood surface defects, this study aims to improve the utilization efficiency of wood in enterprises. …”
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Research on Lightweight Algorithm Model for Precise Recognition and Detection of Outdoor Strawberries Based on Improved YOLOv5n by Xiaoman Cao, Peng Zhong, Yihao Huang, Mingtao Huang, Zhengyan Huang, Tianlong Zou, He Xing

“…The SPPELAN module is added as well to improve the model’s detection efficiency for small objects. The experimental results show that the detection accuracy of the improved model is 98.94%, the recall rate is 99.12%, the model volume is 53.22 MB, and the mAP value is 99.43%. …”
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A Constant False Alarm Rate Detection Method for Sonar Imagery Targets Based on Segmented Ordered Weighting by Wankai Na, Haisen Li, Jian Wang, Jiani Wen, Tianyao Xing, Yuxia Hou

“…Achieving reliable target detection in the field of sonar imagery represents a significant challenge due to the complex underwater interference patterns characterized by speckle noise, tunnel effects, and low-signal-to-noise ratio (SNR) environments. …”
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Infrared Small Target Detection Using Directional Derivative Correlation Filtering and a Relative Intensity Contrast Measure by Feng Xie, Dongsheng Yang, Yao Yang, Tao Wang, Kai Zhang

“…Moreover, the framework maintains low computational complexity, achieving a favorable balance between detection accuracy and efficiency, thereby demonstrating promising potential for deployment in practical IRST scenarios.…”
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Detecting drug transfers via the drop-off method: A supervised model approach using AIS data by Britt van Leeuwen, Maike Nutzel

“…Unlike existing research, primarily employing unsupervised methods, we propose a supervised model specifically tailored to this illicit activity, with a particular emphasis on its application to fishing vessels.Our model significantly reduces the number of data points requiring classification by the observer by 70% , thereby enhancing the efficiency of the drop-off detection process. By employing a Long Short-Term Memory (LSTM) model, our approach demonstrates a change from traditional methods and offers advantages in capturing complex temporal patterns inherent in ‘drop-off’ activities. …”
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Enhancing Real-Time Aerial Image Object Detection with High-Frequency Feature Learning and Context-Aware Fusion by Xin Ge, Liping Qi, Qingsen Yan, Jinqiu Sun, Yu Zhu, Yanning Zhang

“…Aerial image object detection faces significant challenges due to notable scale variations, numerous small objects, complex backgrounds, illumination variability, motion blur, and densely overlapping objects, placing stringent demands on both accuracy and real-time performance. …”
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Automated Digitization Approach for Road Intersections Mapping: Leveraging Azimuth and Curve Detection from Geo-Spatial Data by Ahmad M. Senousi, Wael Ahmed, Xintao Liu, Walid Darwish

“…Effective maintenance and management of road infrastructure are essential for community well-being, economic stability, and cost efficiency. Well-maintained roads reduce accident risks, improve safety, shorten travel times, lower vehicle repair costs, and facilitate the flow of goods, all of which positively contribute to GDP and economic development. …”
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Sensitive detection of dengue serotype-4 on lignin-derived graphene nanofibre and manganese oxide composite by DNA-sensing by Sivainesh Devi Remesh, Saravanan Karuppanan, Veeradasan Perumal, Subash C. B. Gopinath, Mark Ovinis, Pandian Bothi Raja, Natarajan Arumugam, Raju Suresh Kumar

“…Abstract This research addresses the critical challenge of achieving precise DNA detection in complex biological samples by developing a novel, eco-friendly dengue virus serotype 4 biosensor. …”
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Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 by Qing Jiang, Ruipeng Gao, Yan Zhao, Wenzhen Yu, Zhuofan Dang, Shiyi Deng

“…Wear defects occurring on the switch sliding baseplate can give rise to issues such as delayed switch operation, inflexible switching, or even complete failure, thereby escalating the risk of train derailment. Consequently, the detection of wear defects on the switch sliding baseplate is of paramount importance for enhancing traffic efficiency and guaranteeing the safety of train switching operations. …”
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An explainable AI-driven deep neural network for accurate breast cancer detection from histopathological and ultrasound images by Md. Romzan Alom, Fahmid Al Farid, Muhammad Aminur Rahaman, Anichur Rahman, Tanoy Debnath, Abu Saleh Musa Miah, Sarina Mansor

“…However, traditional diagnostic processes relying on manual analysis of medical images are inherently complex and subject to variability between observers, highlighting the urgent need for robust automated breast cancer detection systems. …”
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HCT-Det: A High-Accuracy End-to-End Model for Steel Defect Detection Based on Hierarchical CNN–Transformer Features by Xiyin Chen, Xiaohu Zhang, Yonghua Shi, Junjie Pang

“…These results highlight the model’s effectiveness in improving computational efficiency and detection accuracy for steel surface defect detection.…”
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Attention-Based Dual-Knowledge Distillation for Alzheimer’s Disease Stage Detection Using MRI Scans by Chandita Barman, Sudhanshu Singh, Manob Jyoti Saikia, Shovan Barma

“…This study presents an efficient attention-guided dual-knowledge distillation (D-KD) framework for classifying Alzheimer’s disease (AD) stages using magnetic resonance imaging (MRI) scans based on detection of the subtle anatomical differences. …”
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SFD-YOLO: A novel framework for subsidence funnels detection in China based on large-scale SAR interferograms by Jing Guo, Zhengjia Zhang, Peifeng Ma, Mengmeng Wang, Xuefei Zhang, Dongdong Li, Bing Sui

“…Experimental results demonstrate that the fully trained SFD-YOLO model achieves an mAP50 accuracy of 92.00% while maintaining high efficiency, significantly outperforming other advanced methods. …”
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Slim-sugarcane: a lightweight and high-precision method for sugarcane node detection and edge deployment in natural environments by Lijiao Wei, Lijiao Wei, Shuo Wang, Xinwei Liang, Dongjie Du, Xinyi Huang, Ming Li, Yuangang Hua, Weihua Huang, Zhenhui Zheng, Zhenhui Zheng

“…Accurate detection of sugarcane nodes in complex field environments is a critical prerequisite for intelligent seed cutting and automated planting. …”
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Multi-camera spatiotemporal deep learning framework for real-time abnormal behavior detection in dense urban environments by Sai Babu Veesam, B. Tarakeswara Rao, Zarina Begum, R. S. M. Lakshmi Patibandla, Arvin Arun Dcosta, Shonak Bansal, Krishna Prakash, Mohammad Rashed Iqbal Faruque, K. S. Al-mugren

“…Evaluation on the UCF-Crime, ShanghaiTech and Avenue Datasets showed 40% better false alarm reduction, 50% computational demands lower and an impressive 98% real-time efficiency of this multi-faceted framework. This total framework will enable multi-camera crowd surveillance with adaptive scalability and resource provisioning for real-time dynamic behavioral anomaly detection in real-world settings.…”
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