Lightweight detection algorithms for small targets on unmanned mining trucks by Shuoqi CHENG, Yilihamu·YAERMAIMAITI, Lirong XIE, Xiyu LI, Ying MA

“…It enhances multi-scale feature fusion capability via weighted feature fusion, significantly reducing parameter count while improving small target detection capability. …”
Get full text

Robust UAV Target Tracking Algorithm Based on Saliency Detection by Hanqing Wu, Weihua Wang, Gao Chen, Xin Li

“…In response to this problem, this paper proposes a robust UAV target tracking algorithm based on saliency detection (SDBCF). Using saliency detection methods, the DCF tracker is optimized in three aspects to enhance the robustness of the tracker in complex scenes: feature fusion, filter-model construct, and scale-estimation methods improve. …”
Get full text

Feature selection algorithm based on improved particle swarm joint taboo search by Zhen ZHANG, Peng WEI, Yufeng LI, Julong LAN, Ping XU, Bo CHEN

Subjects: “…intrusion detection…”
Get full text

HSF-DETR: A Special Vehicle Detection Algorithm Based on Hypergraph Spatial Features and Bipolar Attention by Kaipeng Wang, Guanglin He, Xinmin Li

“…Special vehicle detection in intelligent surveillance, emergency rescue, and reconnaissance faces significant challenges in accuracy and robustness under complex environments, necessitating advanced detection algorithms for critical applications. …”
Get full text

A Lightweight Detection Method for Meretrix Based on an Improved YOLOv8 Algorithm by Zhongxu Tian, Sifan Hou, Xiaoxue Yue, Xuewen Hu

“…To address this issue, this paper proposes a lightweight detection method, YOLOv8-RFD, based on an improved YOLOv8 algorithm, tailored for clam sorting applications. …”
Get full text

RTL-Net: real-time lightweight Urban traffic object detection algorithm by Zhiqing Cui, Jiahao Yuan, Haibin Xu, Yamei Wei, Zhenglong Ding

“…Abstract Object detection algorithm in urban traffic using remote sensing images often suffers from high complexity, low real-time performance, and low accuracy. …”
Get full text

FF-YOLO: An Improved YOLO11-Based Fatigue Detection Algorithm for Air Traffic Controllers by Shijie Tan, Weijun Pan, Leilei Deng, Qinghai Zuo, Yao Zheng

“…This paper proposes FF-YOLO, an improved YOLO11-based deep learning algorithm, to detect ATCO fatigue states through facial feature analysis. …”
Get full text

A Bridge Crack Segmentation Algorithm Based on Fuzzy C-Means Clustering and Feature Fusion by Yadong Yao, Yurui Zhang, Zai Liu, Heming Yuan

“…In response to the limitations of traditional image processing algorithms, such as high noise sensitivity and threshold dependency in bridge crack detection, and the extensive labeled data requirements of deep learning methods, this study proposes a novel crack segmentation algorithm based on fuzzy C-means (FCM) clustering and multi-feature fusion. …”
Get full text

Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

Get full text

Research on Lightweight Small Object Detection Algorithm Based on Context Representation by Li Qiang, Cui Jianghui

“…This framework model consists of three parts: a backbone network, a multi-scale feature representation network, and a detection head. …”
Get full text

Research on performance optimizations for TCM-KNN network anomaly detection algorithm by LI Yang1, GUO Li1, LU Tian-bo3, TIAN Zhi-hong1

Subjects: Get full text

Optimal feature‐algorithm combination research for EEG fatigue driving detection based on functional brain network by Yi Zhou, ChangQing Zeng, ZhenDong Mu

“…In this article, the authors propose a functional brain network‐based driving fatigue detection method and seek to combine features and algorithms with optimal effect. …”
Get full text

Photovoltaic fault detection algorithm using ensemble learning enhanced with deep neural network feature engineering by Maryam Parvin, Hossein Yousefi, Behnam Mohammadi-Ivatloo

“…The fault classification was conducted in the second stage using the optimum EL algorithm enhanced with Deep Neural Network (DNN) feature extraction. …”
Get full text

Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm by El-Sayed M. El-Kenawy, Nima Khodadadi, Marwa M. Eid, Ehsaneh Khodadadi, Ehsan Khodadadi, Doaa Sami Khafaga, Amel Ali Alhussan, Abdelhameed Ibrahim, Mohamed Saber

“…In this study, a binary version of the Advanced Al-Biruni Earth Radius (bABER) algorithm is proposed for the intelligent removal of unnecessary data and identifying the most essential features for cancer detection. …”
Get full text

Using Machine Learning Algorithms in Intrusion Detection Systems: A Review by Mazin S. Mohammed, Hasanien Ali Talib

Subjects: Get full text

Lightweight Small Target Detection Algorithm Based on YOLOv8 Network Improvement by Xiaoyi Hao, Ting Li

“…The primary objective of this paper is to address the shortcomings of existing algorithms in the context of UAV-based object detection. …”
Get full text

Laryngeal cancer diagnosis based on improved YOLOv8 algorithm by Xin Nie, Xueyan Zhang, Di Wang, Yuankun Liu, Lumin Xing, Wenjian Liu

“…This study introduces an improved YOLOv8 algorithm named MSEC-YOLO, specifically designed for the detection and classification tasks of laryngeal cancer in endoscopic images. …”
Get full text

Malicious software identification based on deep learning algorithms and API feature extraction by Wei Sun

Subjects: “…Malicious software detection…”
Get full text

CTDA: an accurate and efficient cherry tomato detection algorithm in complex environments by Zhi Liang, Caihong Zhang, Zhonglong Lin, Guoqiang Wang, Xiaojuan Li, Xiangjun Zou

“…To ensure accuracy and efficiency in detecting cherry tomatoes in complex environments, the study proposes a precise, realtime, and robust target detection algorithm: the CTDA model, to support robotic harvesting operations in unstructured environments.MethodsThe model, based on YOLOv8, introduces a lightweight downsampling method to restructure the backbone network, incorporating adaptive weights and receptive field spatial characteristics to ensure that low-dimensional small target features are not completely lost. …”
Get full text

Multi-scale Logo detection algorithm based on convolutional neural network by Yuchao JIANG, Lixin JI, Chao GAO, Shaomei LI

“…Aiming at the requirements for multi-scale Logo detection in natural scene images,a multi-scale Logo detection algorithm based on convolutional neural network was proposed.The algorithm was based on the realization of two-stage object detection.By constructing feature pyramids and adopting layer-by-layer prediction,multi-scale region proposals were generated.The multi-layer feature maps in convolutional neural networks were fused to enhance the feature representation.The experimental results on the FlickrLogos-32 dataset show that compared with the baseline,the proposed algorithm can improve the recall rate of region proposals,and can improve the performance of small Logo detection while ensuring the accuracy of large and middle Logo,proving the superiority of the proposed algorithm.…”
Get full text