Retracted: University Media Content Detection and Classification Based on Information Fusion Algorithm by Advances in Multimedia

Get full text

Advancing Ton-Bag Detection in Seaport Logistics with an Enhanced YOLOv8 Algorithm by Xiulin Qiu, Haozhi Zhang, Chang Yuan, Qinghua Liu, Hongzhi Yao

“…The superiority of the method is verified by comparing it with other classical target detection algorithms.…”
Get full text

An edge detection method of pantograph carbon slide based on an improved Canny algorithm by YANG Jun, GUO Youmin, WANG Jianxin, ZHAO Hongliang

“…Aiming at the problems of inaccurate extraction, discontinuity and being susceptible to noise when the edge of a carbon slide is detected by using a traditional edge detection algorithm, an edge detection method of pantograph carbon slide based on an improved Canny algorithm was proposed in the paper. …”
Get full text

An Efficient Algorithm for Small Livestock Object Detection in Unmanned Aerial Vehicle Imagery by Wenbo Chen, Dongliang Wang, Xiaowei Xie

“…To address this challenge, we propose an efficient Livestock Network (LSNET) algorithm, a novel YOLOv7-based network. Our approach incorporates a low-level prediction head (P2) to detect small objects from shallow feature maps, while removing a deep-level prediction head (P5) to mitigate the effects of excessive down-sampling. …”
Get full text

An Improved YOLOv7-Tiny-Based Algorithm for Wafer Surface Defect Detection by Mengyun Li, Xueying Wang, Hongtao Zhang, Xiaofeng Hu

“…To address the shortcomings of manual inspection and the limitations of existing machine learning methods, this paper proposes a wafer defect detection algorithm based on an improved YOLOv7-tiny. …”
Get full text

Long tunnel group driving fatigue detection model based on XGBoost algorithm by Huazhi Yuan, Kun Zhao, Ying Yan, Li Wan, Zhending Tian, Xinqiang Chen

Subjects: Get full text

Energy-Efficient Fall-Detection System Using LoRa and Hybrid Algorithms by Manny Villa, Eduardo Casilari

Get full text

Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană, Virginia Maria Rădulescu

“…The study systematically classifies these articles by plant type, sensor technology, algorithm category, and diagnostic pipeline (detection, localization, resolution). …”
Get full text

Deep Learning-Based Intelligent Detection Algorithm for Surface Disease in Concrete Buildings by Jing Gu, Yijuan Pan, Jingjing Zhang

Get full text

Detection of Weak Radar Return Signals Based on Pseudo-Time Domain Algorithm by Kaili Wang, Kai Yuan, Bo Bai, Rongxin Tang

Get full text

YOLO-DKM: A Flame and Spark Detection Algorithm Based on Deep Learning by Linpo Shang, Xufei Hu, Zijian Huang, Qiang Zhang, Zhiyu Zhang, Xin Li, Yanzuo Chang

“…In the field of computer vision, existing fire detection algorithms often have problems such as low detection accuracy and algorithm error detection. …”
Get full text

Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

“…Manual diagnosis is labor-intensive and prone to inaccuracies, highlighting the need for automated, accurate detection methods. This study proposes a novel approach for early DR detection by integrating advanced machine learning techniques. …”
Get full text

Auto forensic detecting algorithms of malicious code fragment based on TensorFlow by Binglong LI, Jinlong TONG, Yu ZHANG, Yifeng SUN, Qingxian WANG, Chaowen CHANG

“…In order to auto detect the underlying malicious code fragments in complex，heterogeneous and massive evidence data about digital forensic investigation, a framework for malicious code fragment detecting algorithm based on TensorFlow was proposed by analyzing TensorFlow model and its characteristics.Back-propagation training algorithm was designed through the training progress of deep learning.The underlying binary feature pre-processing algorithm of malicious code fragment was discussed and proposed to address the problem about different devices and heterogeneous evidence sources from storage media and such as AFF forensic containers.An algorithm which used to generate data set about code fragments was designed and implemented.The experimental results show that the comprehensive evaluation index F₁of the method can reach 0.922, and compared with CloudStrike, Comodo, FireEye antivirus engines, the algorithm has obvious advantage in dealing with the underlying code fragment data from heterogeneous storage media.…”
Get full text

YOLO-MMCE algorithm for visual detection of engineering vehicles in high-consequence area by Huimei SUN, Lu LIU, Degang WANG, Taiyong WANG

“…The results revealed precision enhancements in engineering vehicle target detection under real-world conditions, resulting from the YOLOv5 algorithm improvements in three aspects. …”
Get full text

BDK-YOLOv8: An Enhanced Algorithm for UAV Infrared Image Object Detection by Nan Xiao, Xianggong Hong, Zixuan Zheng

“…This paper presents an infrared small object detection algorithm based on YOLOv8n to address challenges like large model size, complex backgrounds, poor small object detection, and scale variations. …”
Get full text

A range spread target detection algorithm based on polarimetric features and SVDD by Qiang LI, Yuanxin YAO, Xiangqi KONG

“…Multi-polarization range high resolution radar is an important mean for ground target detection.In the echo formed by it, the target occupies multiple range cells and becomes an extended target.The traditional spread target detection method relies on energy, and the detection performance decreases when the signal-to-clutter ratio decreases.A spread target detection algorithm based on polarization decomposition features was proposed, which improved the detection performance under low signal-to-clutter ratio by using the difference of polarization scattering characteristics between target and clutter.Specifically, 16 kinds of polarization decomposition features were extracted to form feature vectors as detection statistics, and then support vector data description (SVDD) was used to obtain the detection threshold.When training the detection threshold, the polarization decomposition features of clutter were extracted as training data.In order to ensure the false alarm probability, two penalty parameters were introduced into the objective function of SVDD.The experimental results show that the proposed method requires a signal-to-clutter ratio of about 12.6 dB in the case of Gobi background, false alarm probability of 10^-4 and detection probability of 90%, which is about 1.7 dB lower than the energy-based methods.…”
Get full text

Pitfalls in users’ evaluation of algorithms for text-based similarity detection in medical education by Jakub Ščavnický, Matěj Karolyi, Petra Růžičková, Andrea Pokorná, Hana Harazim, Petr Štourač, Martin Komenda

Get full text

A Proposed Algorithm to Detect the Effect of an Object Within a Video Series by Abeer Thanoon

“…In this research an algorithm for detecting a specific object and tracing its movement within a depicted series is proposed . …”
Get full text

Intrusion detection algorithm of wireless network based on network traffic anomaly analysis by Xiangqian Nie, Jiao Xing, Qimeng Li, Fan Xiao

“…These features are analyzed by an intrusion detection module combining particle swarm optimization and support vector machine algorithms. …”
Get full text

Step-by-step classification detection algorithm of SPPM based on K-means clustering by Huiqin WANG, Wenbin HOU, Qingbin PENG, Minghua CAO, Rui HUANG, Ling LIU

“…In view of the high computational complexity in spatial pulse position modulation systems when using maximum likelihood detection algorithm, a step-by-step classification detection algorithm based on K-means clustering was proposed according to the characteristics of signal matrix with spatial pulse position modulation.The signal vector detection algorithm was utilized to detect the index of light source in the training samples.The on K-means clustering algorithm was utilized to acquire the mapping rule between centroid of samples and modulated symbol by offline training.Subsequently, online detection of modulated symbols was achieved based on the mapping rule, and then the index of light sources was detected by exhaustive search.In addition, Monte Carlo method was used to investigate the effects of key parameters such as the number of clusters and initialization times on the system bit error rate (BER) performance.Simulation results demonstrate that the proposed algorithm can achieve an approximate BER performance as the maximum likelihood algorithm on the basis of greatly reducing the computational complexity.Compared with the linear decoding algorithms, the proposed algorithm is also applicable to scenarios where the number of detectors is less than the number of light sources.…”
Get full text