Detection Algorithm for Air Duct Clamp on Trains Based on RSA-YOLOv10n by WANG Dairong, ZHAO Yuhong, QU Xiaozhang, LIU Yi

“…To address challenges in the detection of air duct clamps due to factors such as dim environments and small objects in train detection, such as insufficient detection accuracy and low detection efficiency, this paper proposes a RSA-YOLOv10n-based detection algorithm, developed utilizing a dataset of air duct clamps collected from trains. …”
Get full text

Robust scale fusion and edge-aware feature attention network for remote sensing UAV road detection under harsh weather by Jialang Liu, Jialei Zhan, Jiehua Zhang, Jiangming Chen, Yan Song, Lixing Tang, Le Zhou, Chengsi Du, Yingmei Wei, Yanming Guo

“…The model also maintains a competitive inference speed of 23.2 FPS, demonstrating a strong balance between accuracy and efficiency. These results highlight both the effectiveness of RSFC-EAFANet and the importance of weather-aware benchmarks for advancing UAV-based road detection. …”
Get full text

Integrating attention mechanism and boundary detection for building segmentation from remote sensing images by Ping Liu, Yu Gao, Xiangtian Zheng, Hesong Wang, Yimeng Zhao, Xinru Wu, Zehao Lu, Zhichuan Yue, Yuting Xie, Shufeng Hao

“…The module captures image feature information in the channel dimension using a one-dimensional convolutional cross-channel method and automatically adjusts the cross-channel dimension using adaptive convolutional kernel size. Additionally, a weighted boundary loss function is designed to replace the traditional semantic segmentation cross-entropy loss to detect the boundary of a building. …”
Get full text

DAU-YOLO: A Lightweight and Effective Method for Small Object Detection in UAV Images by Zeyu Wan, Yizhou Lan, Zhuodong Xu, Ke Shang, Feizhou Zhang

“…However, drone images typically exhibit challenges such as small object sizes, dense distributions, and high levels of overlap. Traditional object detection networks struggle to achieve the required accuracy and efficiency under these conditions. …”
Get full text

Modeling the behavior of a generalized Cholera epidemic model with asymptomatic measures for early detection. by Ali Hasan Ali, Aqeel Ahmad, Fakher Abbas, Evren Hincal, Abdul Ghaffar, Belal Batiha, Husam A Neamah

“…It has been confirmed that individuals with strong immune systems will recover efficiently if the infection is diagnosed early through timely detection measures. …”
Get full text

Enhanced YOLOv5s Model for Improved Multi-Sized Object Detection in Road Scenes by Sangavi Sivanandham, Dharanibai Gunaseelan

“…Furthermore, an efficient channel attention (ECA) mechanism is integrated into the backbone to prioritize key feature channels, thereby enhancing the model’s ability to detect overlapping and small objects. …”
Get full text

A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM by Guoli Song, Zheng Huang, Yiwen Zhao, Xingang Zhao, Yunhui Liu, Min Bao, Jianda Han, Peng Li

“…The conventional artificial diagnosis is time-consuming and relies on the clinical experience of radiologists. To detect gliomas more efficiently, this paper proposes a noninvasive automatic diagnosis system for gliomas based on the machine learning methods. …”
Get full text

Multiscale Edge Enhancement and Progressive Change-Aware Network for Remote Sensing Change Detection by Yan Xing, Jiali Hu, Yunan Jia, Rui Huang

“…Change detection (CD) in remote sensing (RS) images serves as a vital method for identifying changes on the Earth’s surface. …”
Get full text

LKD-YOLOv8: A Lightweight Knowledge Distillation-Based Method for Infrared Object Detection by Xiancheng Cao, Yueli Hu, Haikun Zhang

“…Nonetheless, the limited computational power of edge devices presents a considerable challenge in achieving an optimal balance between accuracy and computational efficiency in infrared object detection. In order to enhance the accuracy of infrared target detection and strengthen the implementation of robust models on edge platforms for rapid real-time inference, this paper presents LKD-YOLOv8, an innovative infrared object detection method that integrates YOLOv8 architecture with masked generative distillation (MGD), further augmented by the lightweight convolution design and attention mechanism for improved feature adaptability. …”
Get full text

A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n by Fengwu Zhu, Suyu Wang, Min Liu, Weijie Wang, Weizhi Feng

“…The proposed model exhibits significant advantages in terms of lightweight design and improved detection efficiency, demonstrating substantial potential for practical deployment. …”
Get full text

Revolutionizing prostate cancer diagnosis: Unleashing the potential of an optimized deep belief network for accurate Gleason grading in histological images by S. Angel Latha Mary, S. Siva Subramanian, G. Priyanka, T. Vijayakumar, Suganthi Alagumalai

“…PC (Prostate Cancer) is the second highest cause of death due to cancer in men globally. Proper detection and treatment are critical for halting or controlling the growth and spread of cancer cells within the human organism. …”
Get full text

Lightweight detection and segmentation of crayfish parts using an improved YOLOv11n segmentation model by Wei Shi, Jun Zhang, YunFan Fu, DanWei Chen, JianPing Zhu, ChunFeng Lv

“…We propose YOLOv11nDHBC, a lightweight detection and segmentation framework that integrates three technical innovations. …”
Get full text

Detecting Potential Investors in Crypto Assets: Insights from Machine Learning Models and Explainable AI by Timotej Jagrič, Davor Luetić, Damijan Mumel, Aljaž Herman

Get full text

TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…In automatic driving systems, accurate and efficient object detection is essential to ensure driving safety and improve the driving experience. …”
Get full text

Re-Parameterization After Pruning: Lightweight Algorithm Based on UAV Remote Sensing Target Detection by Yang Yang, Pinde Song, Yongchao Wang, Lijia Cao

“…Consequently, this paper presents a refined iteration of the lightweight object detection algorithm to address the above issues. The MobileNetV3 based on the efficient channel attention (ECA) module is used as the backbone network of the model. …”
Get full text

Quantized Auto Encoder-Based Anomaly Detection for Multivariate Time Series Data in 5G Networks by Giovanni Trappolini, Antonio Purificato, Federico Siciliano, Luigi D'Addona, Anna Maria Spagnolo, Domenico Dato, Fabrizio Silvestri

“…We provide a detailed evaluation of our model across 5G data scenarios, demonstrating its enhanced accuracy and efficiency in anomaly detection compared to existing state-of-the-art methods, with gains of up to 8%.…”
Get full text

YOLOv10-kiwi: a YOLOv10-based lightweight kiwifruit detection model in trellised orchards by Jie Ren, Wendong Wang, Yuan Tian, Jinrong He

“…YOLOv10-Kiwi offers an efficient solution for automated kiwifruit detection on low-power agricultural robots.…”
Get full text

A Novel Algorithm for Adaptive Detection and Tracking of Extended Targets Using Millimeter-Wave Imaging Radar by Ge Zhang, Weimin Shi, Xiaofeng Shen, Qilong Miao, Chenfei Xie, Lu Chen

“…The initial target distribution is estimated using two-dimensional kernel density estimation (2D-KDE). Compared to existing ET tracking algorithms, the proposed SPS method demonstrates superior universality in accommodating diverse scattering point distributions and integrates detection and tracking into a unified process, thereby significantly improving information utilization efficiency. …”
Get full text

Enhanced convolutional neural networks for defect detection in fiber-reinforced composites: a hyperparameter optimization approach by Pankaj Beldar, Rasika Chandramore, Sarika Jagtap, Dipali Bendale

Get full text

Oriented Road Marking Detection in MLS Point Cloud Intensity Images Using Channel and Spatial Attention by Dehui Li, Tao Liu, Ping Du, Yi He, Shuangtong Liu

“…The proposed method achieves an mAP of 84.7% on Test Set I, representing a 3.2% improvement over the baseline model, while maintaining high efficiency, offering a robust and reliable solution for real-time road marking detection tasks.…”
Get full text