Adaptive Multi-Radar Anti-Bias Track Association Algorithm Based on Reference Topology Features by Shaoming Wei, Xuan Zhou, Jun Wang, Rui Pang, Xueqing Li, Qiang Liu

“…To address the track association problem in multi-radar systems, particularly the challenges posed by offset bias, this paper proposes an adaptive multi-radar anti-bias track association algorithm based on reference topological features (RETs) that achieves accurate association despite offset bias and radar missed detections. …”
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Plug-and-Play Robust Aerial Object Detection Under Hazy Conditions by Wei Wu, Hao Chang, Zhiwen Chen, Zhu Li

“…Moreover, we also propose a detection feature pyramid loss function to more accurately restore object features. …”
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Mine underground object detection algorithm based on TTFNet and anchor-free by Song Zhen, Qing Xuwen, Zhou Meng, Men Yuting

“…To solve the problem of poor object detection effect caused by uneven light and high noise in underground mines, this study proposes a TTFNet (training-time-friendly network)-based object detection algorithm for underground mines. …”
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Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features by Xiaorong Zhang, Siyuan Li, Zhongyang Xing, Binliang Hu, Xi Zheng

“…The high-resolution spatial features are first employed for detecting scale-invariant features, while the spectral information is used for matching, and then the idea of image stitching is employed to fuse the image after fine registration to obtain high-precision registration results. …”
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RMFKAN: Network Spammers Detection Method Based on Improved Graph Mamba by WANG Yuzhe, YAN Jinghua, BU Fanliang, WANG Yifan, LI Jia, HAN Zhuxuan

“…The method of heterogeneous perception long-distance relationship feature extraction is used to solve the problem of feature loss in long-distance relationships across communities in large-scale social networks. …”
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Research on Vehicle Target Detection Method Based on Improved YOLOv8 by Mengchen Zhang, Zhenyou Zhang

“…To improve the performance of vehicle target detection in complex traffic environments and solve the problem that it is difficult to make a lightweight detection model, this paper proposes a lightweight vehicle detection model based on enhanced You Only Look Once v8. …”
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An efficient network for object detection in scale-imbalanced remote sensing images by Li Zhongyu, Jing Xiaoping, Sun Rui, Yang Yazhi, Wang Wei, Zhu Hongzhen

“…To address this problem, this article proposes a detection method for multi-scale remote sensing image targets by combining the frequency attention mechanism. …”
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IMP‐DETR: Optimization model for defect detection of injection‐moulded products by Anzhan Liu, Lei Han

“…Additionally, the Conv3XC‐Fusion module is designed to resolve the problem of integrating multi‐scale features, improving the stability of detection. …”
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Bilingual hate speech detection on social media: Amharic and Afaan Oromo by Teshome Mulugeta Ababu, Michael Melese Woldeyohannis, Emuye Bawoke Getaneh

“…The FastText feature extraction overcomes the problem of out of vocabulary (OOV). …”
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TFC: A Series of Band Selection Methods for Hyperspectral Target Detection by Qianghui Wang, Xikui Miao, Enze Guo, Tao Zhao

“…Its idea is derived from the target-constrained interference-minimized filter (TCIMF). By analyzing the detection principle of TCIMF, the BS problem can be transformed into a constrained optimization problem. …”
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PA-YOLO-Based Multifault Defect Detection Algorithm for PV Panels by Wang Yin, Zhao Jingyong, Xie Gang, Zhao Zhicheng, Hu Xiao

“…For the occlusion problem of dense targets in the dataset, we introduce a repulsive loss function, which successfully reduces the occurrence of false detection situations. …”
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Problems of documenting medieval epigraphic monuments of North Caucasus (using the example of the Karachay-Cherkessian Republic) by Laura A. Nagoeva

“…The accumulated research experience is considered and the main methods of fixing and documenting the detected objects are characterized. The features of the interpretation of these monuments in the scientific literature and several key methodological problems are identified. …”
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GSB: GNGS and SAG-BiGRU network for malware dynamic detection. by Zhanhui Hu, Guangzhong Liu, Xinyu Xiang, Yanping Li, Siqing Zhuang

“…However, the minority categories' attacks will bring great losses to countries, enterprises, or individuals. For solving the problem, this study proposed the GNGS algorithm to construct a new balance dataset for the model algorithm to pay more attention to the feature learning of the minority attacks' malware to improve the detection rate of attacks' malware. …”
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A hybrid approach of vision transformers and CNNs for detection of ulcerative colitis by Syed Abdullah Shah, Imran Taj, Syed Muhammad Usman, Syed Nehal Hassan Shah, Ali Shariq Imran, Shehzad Khalid

“…Researchers have proposed variety of machine/deep learning methods for automated detection of ulcerative colitis, however, several challenges exists including class imbalance problem, comprehensive feature extraction and accurate classification. …”
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An intelligent spam detection framework using fusion of spammer behavior and linguistic. by Amna Iqbal, Muhammad Younas, Muhammad Kashif Hanif, Muhammad Murad, Rabia Saleem, Muhammad Aater Javed

“…The problem statement of this research paper revolves around addressing challenges concerning feature selection and evolving spammer behavior and linguistic features, with the goal of devising an efficient model for spam detection. …”
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Fault detection and diagnosis method for heterogeneous wireless network based on GAN by Xiaorong ZHU, Peipei ZHANG

“…Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.…”
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Elfimova. MicroRNA: a clinician’s view of the state of the problem. Part 1. History of the issue by O. Iu. Mironova, M. V. Berdysheva, E. M. Elfimova

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Advancing Nighttime Object Detection through Image Enhancement and Domain Adaptation by Chenyuan Zhang, Deokwoo Lee

“…Due to the lack of annotations for nighttime low-light images, object detection in low-light images has always been a challenging problem. …”
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Fault detection and diagnosis method for heterogeneous wireless network based on GAN by Xiaorong ZHU, Peipei ZHANG

“…Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.…”
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A Small Target Pedestrian Detection Model Based on Autonomous Driving by Yang Zhang, Shuaifeng Zhang, Dongrong Xin, Dewang Chen

“…Then, feature selection and feature alignment modules are added to the lateral connection part of the feature pyramid to enhance important pedestrian features in the input image, and the multiscale feature fusion capability of the model is enhanced for small-target pedestrians, thereby improving the detection accuracy of small-target pedestrians and solving the problems of feature misalignment and ignored multiscale features in the feature pyramid network. …”
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