A Video SAR Multi-Target Tracking Algorithm Based on Re-Identification Features and Multi-Stage Data Association by Anxi Yu, Boxu Wei, Wenhao Tong, Zhihua He, Zhen Dong

“…The algorithm extracts high-dimensional ReID features using the Dense-Net121 network for enhanced shadow detection and calculates a cost matrix by integrating ReID feature cosine similarity with Intersection over Union similarity. …”
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SMA-YOLO: An Improved YOLOv8 Algorithm Based on Parameter-Free Attention Mechanism and Multi-Scale Feature Fusion for Small Object Detection in UAV Images by Shenming Qu, Chaoxu Dang, Wangyou Chen, Yanhong Liu

“…Consequently, we propose a UAV image small object detection algorithm, termed SMA-YOLO. Firstly, a parameter-free simple slicing convolution (SSC) module is integrated in the backbone network to slice the feature maps and enhance the features so as to effectively retain the features of small objects. …”
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Application of microscopic image processing and artificial intelligence detecting and classifying the spores of three novel species of Trichoderma by Fatemeh Soltani Nezhad, Kamran Rahnama, Seyed Mohamad Javidan, Keyvan Asefpour Vakilian

“…In this study, a microscopic image dataset has been developed, followed by identifying and classifying the spores of three Trichoderma species including T. harzianum, T. atroviride, and T. virens using microscopic image processing techniques. The genetic algorithm was used to identify the most effective visual features for spore classification, including color, texture, and shape. …”
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Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…This study presents a novel Computer-Aided Diagnosis of Haematologic Disorders Detection Based on Spatial Feature Learning Networks with Hybrid Model (CADHDD-SFLNHM) approach using Blood Cell Images. …”
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Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

“…Furthermore, while feature selection benefits simpler algorithms (such as RF), normalization is more useful for complex algorithms like ANNs and deep neural networks (DNNs), and algorithms such as Naive Bayes are unsuitable for IDS modeling. …”
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Vehicle detection and classification for traffic management and autonomous systems using YOLOv10 by Anning Ji, Xintao Ma

Subjects: “…Real-time vehicle detection…”
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Application of deconvolutional networks for feature interpretability in epilepsy detection by Sihao Shao, Yu Zhou, Ruiheng Wu, Aiping Yang, Qiang Li

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MC-ASFF-ShipYOLO: Improved Algorithm for Small-Target and Multi-Scale Ship Detection for Synthetic Aperture Radar (SAR) Images by Yubin Xu, Haiyan Pan, Lingqun Wang, Ran Zou

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Lightweight Deepfake Detection Based on Multi-Feature Fusion by Siddiqui Muhammad Yasir, Hyun Kim

“…In order to reduce the computational burden usually associated with DL models, our method integrates machine learning classifiers in combination with keyframing approaches and texture analysis. Moreover, the features extracted with a histogram of oriented gradients (HOG), local binary pattern (LBP), and KAZE bands were integrated to evaluate using random forest, extreme gradient boosting, extra trees, and support vector classifier algorithms. …”
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Drowsiness Detection in Drivers Using Facial Feature Analysis by Ebenezer Essel, Fred Lacy, Fatema Albalooshi, Wael Elmedany, Yasser Ismail

“…Despite considerable research in this area, this paper aims to improve the precision of drowsiness detection specifically for long-haul travel by employing the Dlib-based facial feature detection algorithm. …”
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Research on Classification of Rail Defects Based on Image Processing Algorithm by Mengying HUANG, Jiangping LUO, Wenxing WANG, Jingwei CAO

“…Therefore, a classification for rail defects based on image processing algorithm was proposed. Firstly, the Tamura texture feature algorithm was combined with the local binary pattern algorithm to extract the feature values of the defect images, and form feature vectors. …”
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Ship Detection Transformer in SAR Images Based on Key Scattering Points Feature Aggregation and Context Feature Refinement by Yifei Yin, Zhu Yang, Hao Shi, Fanyu Meng, Wei Li

“…In recent years, deep learning algorithms have demonstrated significant advancements in the field of ship detection using synthetic aperture radar (SAR). …”
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Intelligent Detection of Oceanic Front in Offshore China Using EEFD-Net with Remote Sensing Data by Ruijie Kong, Ze Liu, Yifei Wu, Yong Fang, Yuan Kong

Subjects: “…automatic detection algorithm…”
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Salient Object Detection Based on Background Feature Clustering by Kan Huang, Yong Zhang, Bo Lv, Yongbiao Shi

“…We model the background distribution based on feature clustering algorithm, which allows for fully exploiting statistical and structural information of the background. …”
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Detection of Pathogenic Microorganisms by Fusion of Recursive Feature Pyramid by HUANGZhitian, XIEYining, ZHAOJing, HEYongjun

“…Aiming at the problems of less research on the detection of pathogenic microorganisms , large differences in target size and complex background , a multi-scale detection method of pathogenic microorganisms fused with recursive feature pyramid was proposed. …”
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Interfered feature elimination coupled with feature group selection for wound infection detection by electronic nose. by Jia Liu, Jinglei Zhang, Shaoqi Zhang, Kaiwei Li, Xiang Li, Shuo Zhang, Hang Gu, Zhen Chen, Chao Liu, Nan Zhang, Tong Sun

“…In this method, the IFE algorithm first removed the bad sensor features; then the FGS algorithm determined the optimized sensor combination by gradually selecting the features in groups. …”
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Small Object Detection Algorithm Based on Partial Convolution and Attention Fusion Detection Head by Peng Sheng, Zhu Fenghua, Zhou Jin, Zhu Gaofeng, Wang Yingxu, Chen Yuehui

“…This paper proposes a small object detection algorithm based on partial convolution and attention fusion detection head, aiming to address the limitations of current mainstream object detection algorithms in detecting small objects in aerial images. …”
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Grasp Detection under Occlusions Using SIFT Features by Zhaojun Ye, Yi Guo, Chengguang Wang, Haohui Huang, Genke Yang

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EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection by Haojie Chen, Lumei Su, Riben Shu, Tianyou Li, Fan Yin

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Dust detection algorithm based on improved YOLOv5 by Qinghua CHEN, Junwei ZHANG, Yingsong CHENG, Xu ZHANG, Jianhua CHENG

“…In view of this, we propose a dust image detection method based on the improved YOLOv5 algorithm. …”
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