Research on Multi-Objective Pedestrian Tracking Algorithm Based on Full-Size Feature Fusion by Yihuai Zhu, Zhandong Liu, Ke Li, Yong Li, Xiangwei Qi, Nan Ding

“…In the field of Multi-Object Tracking (MOT), the current mainstream approach is the tracking by detection paradigm, which heavily relies on the accuracy of the detector, the comprehensiveness of feature extraction, and the superiority of the data association matching algorithm. …”
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A Multi-Objective Bio-Inspired Optimization for Voice Disorders Detection: A Comparative Study by Maria Habib, Victor Vicente-Palacios, Pablo García-Sánchez

“…Different multi-objective evolutionary algorithms (the Non-dominated Sorting Genetic Algorithm (NSGA-II), Strength Pareto Evolutionary Algorithm (SPEA-II), and the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D)) have been compared to detect voice disorders by optimizing two conflicting objectives: error rate and the number of features. …”
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LocaLock: Enhancing Multi-Object Tracking in Satellite Videos via Local Feature Matching by Lingyu Kong, Zhiyuan Yan, Hanru Shi, Ting Zhang, Lei Wang

“…Multi-object tracking (MOT) in satellite videos is a challenging task due to the small size and blurry features of objects, which often lead to intermittent detection and tracking instability. …”
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Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

“…Multi-object tracking still faces significant challenges in complex conditions such as dense scenes, occlusion environments, and non-linear motion, especially regarding the detection and identity maintenance of small objects. …”
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Enhanced multi-object tracking via appearance feature gating using UMAP by Ken Arioka, Yuichi Sawada

“…The core idea is to leverage the Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction to analyze high-dimensional appearance features, facilitating comparisons in a 2D space. By evaluating the similarity between objects in existing tracks and newly detected candidates, our method effectively identifies and corrects incorrect data associations. …”
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A review: Multi-Objective Algorithm for Community Detection in Complex Social Networks by Mariwan Wahid Ahmed, Kamaran Faraj

“…Recently, research on multi-objective optimization algorithms for community detection in complex networks has grown considerably. …”
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Multi-Frame Joint Detection Approach for Foreign Object Detection in Large-Volume Parenterals by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

Subjects: “…object detection…”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

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Multi-object detection for underground unmanned locomotives based on DYCS-YOLOv8n by XU Jinhui, WANG Wenshan, WANG Shuang, WANG Wenyue, ZHAO Tingting

“…To address the challenges in underground unmanned locomotive image feature extraction—such as poor lighting, high noise, and motion blur, which result in the loss of image details and difficulty in identifying small targets—a multi-object detection model for underground unmanned locomotives based on DYCS-YOLOv8n was proposed. …”
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Embedded Descriptor Generation in Faster R-CNN for Multi-Object Tracking by Younis Younis, Khalil Alsaif

“…With the rapid growth of computer usage to extract the required knowledge from a huge amount of information, such as a video file, significant attention has been brought towards multi-object detection and tracking. Artificial Neural Networks (ANNs) have shown outstanding performance in multi-object detection, especially the Faster R-CNN network. …”
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A Swarm-Based Multi-Objective Framework for Lightweight and Real-Time IoT Intrusion Detection by Hessah A. Alsalamah, Walaa N. Ismail

“…MOOIDS-IoT combines a Genetic Algorithm (GA)-based feature selection technique with a multi-objective Particle Swarm Optimization (PSO) algorithm. …”
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Single-Task Joint Learning Model for an Online Multi-Object Tracking Framework by Yuan-Kai Wang, Tung-Ming Pan, Chi-En Hu

“…Multi-object tracking faces critical challenges, including occlusions, ID switches, and erroneous detection boxes, which significantly hinder tracking accuracy in complex environments. …”
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Re-identification assistance and multi-stage association for pedestrian multi-object tracking by Ye Li, Li Zhan, Lei Wu, Hongkun Liu, Jianli Min, Xinzhong Wang

“…Therefore, we design a multi-object pedestrian tracking method that combines re-identification feature assistance and multi-stage data association (RAMA). …”
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Integrating Viewing Direction and Image Features for Robust Multi-View Multi-Object 3D Pedestrian Tracking by R. Ali, M. Mehltretter, C. Heipke

“…Recently, there has been growing interest in the development of 3D multi-view, multi-object detection and tracking models (MV-MOD and MV-MOT), resulting in significant methodological advances. …”
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A multi-object detection method for building fire warnings through artificial intelligence generated content by Jingwei Fu, Zhen Xu, Qingrui Yue, Jiarui Lin, Ning Zhang, Yujie Zhao, Donglian Gu

“…Subsequently, a multi-object detection model is developed to enhance its feature capture capability, by incorporating the MLCA mechanism into its backbone and replacing the feature fusion layer in its neck. …”
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A Robust Multi‐Objective Pressure Sensor Placement Method for Burst Detection in Water Distribution Systems by Kun Du, Jinxin Yu, Feifei Zheng, Wei Xu, Dragan Savic, Zoran Kapelan

“…This consequently hinders the wide application of existing PSP methods for burst detection in WDSs. This study proposes a novel multi‐objective PSP method aimed at maximizing burst detection while minimizing the number of sensors. …”
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A Dynamic Kalman Filtering Method for Multi-Object Fruit Tracking and Counting in Complex Orchards by Yaning Zhai, Ling Zhang, Xin Hu, Fanghu Yang, Yang Huang

“…To address these challenges, this paper proposes a multi-object fruit tracking and counting method, which integrates an improved YOLO-based object detection algorithm with a dynamically optimized Kalman filter. …”
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MOMFNet: A Deep Learning Approach for InSAR Phase Filtering Based on Multi-Objective Multi-Kernel Feature Extraction by Xuedong Zhang, Cheng Peng, Ziqi Li, Yaqi Zhang, Yongxuan Liu, Yong Wang

“…To address this issue, this study proposes MOMFNet, a deep learning approach for InSAR phase filtering based on multi-objective multi-kernel feature extraction that leverages multi-objective multi-kernel feature extraction. …”
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On-Satellite Implementation of Real-Time Multi-Object Moving Vehicle Tracking with Complex Moving Backgrounds by Jingyi Yu, Siyuan Wei, Yuxiao Wen, Danshu Zhou, Runjiang Dou, Xiuyu Wang, Jiangtao Xu, Jian Liu, Nanjian Wu, Liyuan Liu

“…We use feature matching to effectively eliminate the effects of background motion and use the neighborhood pixel difference method to extract moving vehicle targets in the detection stage. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

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