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A Comparative Study of YOLO Series (v3–v10) with DeepSORT and StrongSORT: A Real-Time Tracking Performance Study

https://doi.org/10.3390/electronics14050876

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-031-72751-1_1openalex-snapshot

YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot

Microsoft COCO: Common Objects in Context

inferredcites →https://doi.org/10.1007/978-3-319-48881-3_2openalex-snapshot

Performance Measures and a Data Set for Multi-target, Multi-camera Tracking

inferredcites →https://doi.org/10.1007/978-981-97-1087-4_41openalex-snapshot

Detection of Occlusion-Resistant Based on Improved YOLOv7

inferredcites →https://doi.org/10.1007/978-981-99-7962-2_39openalex-snapshot

A Review on YOLOv8 and Its Advancements

inferredcites →https://doi.org/10.1007/s00521-021-05978-9openalex-snapshot

Poly-YOLO: higher speed, more precise detection and instance segmentation for YOLOv3

inferredcites →https://doi.org/10.1007/s00521-023-08809-1openalex-snapshot

An improved fire detection approach based on YOLO-v8 for smart cities

inferredcites →https://doi.org/10.1007/s11263-009-0275-4openalex-snapshot

The Pascal Visual Object Classes (VOC) Challenge

inferredcites →https://doi.org/10.1007/s11263-020-01375-2openalex-snapshot

HOTA: A Higher Order Metric for Evaluating Multi-object Tracking

inferredcites →https://doi.org/10.1007/s11554-024-01545-2openalex-snapshot

YOLO9tr: a lightweight model for pavement damage detection utilizing a generalized efficient layer aggregation network and attention mechanism

inferredcites →https://doi.org/10.1016/s0968-090x(98)00019-9openalex-snapshot

A real-time computer vision system for vehicle tracking and traffic surveillance

inferredcites →https://doi.org/10.1049/itr2.12190openalex-snapshot

A domain‐adaptive method with cycle perceptual consistency adversarial networks for vehicle target detection in foggy weather

inferredcites →https://doi.org/10.1056/nejmp1716891openalex-snapshot

Bedside Computer Vision — Moving Artificial Intelligence from Driver Assistance to Patient Safety

inferredcites →https://doi.org/10.1109/access.2022.3154474openalex-snapshot

Improved YOLOv4 Based on Attention Mechanism for Ship Detection in SAR Images

inferredcites →https://doi.org/10.1109/cvidliccea56201.2022.9824495openalex-snapshot

Lightweight the Focus module in YOLOv5 by Dilated Convolution

inferredcites →https://doi.org/10.1109/cvpr.2014.81openalex-snapshot

Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot

Going deeper with convolutions

inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot

You Only Look Once: Unified, Real-Time Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2017.690openalex-snapshot

YOLO9000: Better, Faster, Stronger

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00165openalex-snapshot

GhostNet: More Features From Cheap Operations

inferredcites →https://doi.org/10.1109/cvpr46437.2021.01625openalex-snapshot

Bottleneck Transformers for Visual Recognition

inferredcites →https://doi.org/10.1109/cvpr52729.2023.00721openalex-snapshot

YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors

inferredcites →https://doi.org/10.1109/cvprw50498.2020.00203openalex-snapshot

CSPNet: A New Backbone that can Enhance Learning Capability of CNN

inferredcites →https://doi.org/10.1109/icassp49357.2023.10097155openalex-snapshot

Yolo-Based Lightweight Object Detection With Structure Simplification And Attention Enhancement

inferredcites →https://doi.org/10.1109/iceca55336.2022.10009122openalex-snapshot

Multi-Scale Features Fusion with YOLOv3 for Detecting Small and Fine Tumors in MRI images

inferredcites →https://doi.org/10.1109/icip.2017.8296962openalex-snapshot

Simple online and realtime tracking with a deep association metric

inferredcites →https://doi.org/10.1109/icnlp52887.2021.00036openalex-snapshot

YOLOv3 Target Detection Algorithm Based on Channel Attention Mechanism

inferredcites →https://doi.org/10.1109/jsen.2020.3041615openalex-snapshot

Multi-Object Detection and Tracking, Based on DNN, for Autonomous Vehicles: A Review

inferredcites →https://doi.org/10.1109/tmm.2023.3240881openalex-snapshot

StrongSORT: Make DeepSORT Great Again

inferredcites →https://doi.org/10.1155/2008/246309openalex-snapshot

Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics

inferredcites →https://doi.org/10.3233/jifs-224530openalex-snapshot

An advanced YOLOv3 method for small object detection

inferredcites →https://doi.org/10.3390/agronomy13071824openalex-snapshot

A Lightweight YOLOv8 Tomato Detection Algorithm Combining Feature Enhancement and Attention

inferredcites →https://doi.org/10.3390/app14178054openalex-snapshot

Engineering Vehicle Detection Based on Improved YOLOv6

inferredcites →https://doi.org/10.3390/electronics10060730openalex-snapshot

Computer Vision Meets Educational Robotics

inferredcites →https://doi.org/10.3390/electronics12102161openalex-snapshot

Accelerating the Response of Self-Driving Control by Using Rapid Object Detection and Steering Angle Prediction

inferredcites →https://doi.org/10.3390/plants11233260openalex-snapshot

A Multiscale Lightweight and Efficient Model Based on YOLOv7: Applied to Citrus Orchard

inferredcites →https://doi.org/10.3390/rs13091619openalex-snapshot

A Real-Time Apple Targets Detection Method for Picking Robot Based on Improved YOLOv5

inferredcites →https://doi.org/10.3390/s22155817openalex-snapshot

SF-YOLOv5: A Lightweight Small Object Detection Algorithm Based on Improved Feature Fusion Mode

inferredcites →https://doi.org/10.3390/s23125539openalex-snapshot

YOLO-GW: Quickly and Accurately Detecting Pedestrians in a Foggy Traffic Environment

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-18042-1_12openalex-snapshot

Comparative Study of Deep Learning Models for Real-Time Detection and Tracking in Football

inferred← citeshttps://doi.org/10.1007/978-3-032-34384-0_31openalex-snapshot

Autonomous Flight System for UAVs to Selected Objects

inferred← citeshttps://doi.org/10.1007/s11282-025-00878-3openalex-snapshot

Diagnostic performance of artificial intelligence for facial fracture detection: a systematic review

inferred← citeshttps://doi.org/10.1016/j.atech.2025.101280openalex-snapshot

Real-time pest monitoring with RSCDet: Deploying a novel lightweight detection model on embedded systems

inferred← citeshttps://doi.org/10.1109/icpcsn68523.2026.11543895openalex-snapshot

Vision-based Vehicle Speed Estimation using Faster R-CNN and Deep Sort Techniques

inferred← citeshttps://doi.org/10.1109/smc58881.2025.11342845openalex-snapshot

YOLO-CCOF: An Algorithm for Aluminum Defect Detection Based on Improved YOLOv8

inferred← citeshttps://doi.org/10.17780/ksujes.1735791openalex-snapshot

ENDÜSTRİYEL SAHALARDA İŞ GÜVENLİĞİ İÇİN YOLO-V8 VE DEEPSORT İLE BİR DERİN GÖRÜ ÇALIŞMASI

inferred← citeshttps://doi.org/10.2139/ssrn.5381775openalex-snapshot

Diagnostic Performance of Artificial Intelligence for Facial Fracture Detection: A Systematic Review

inferred← citeshttps://doi.org/10.3390/app15137137openalex-snapshot

Food Waste Detection in Canteen Plates Using YOLOv11

inferred← citeshttps://doi.org/10.3390/asi8060190openalex-snapshot

Decision Support System for Wind Farm Maintenance Using Robotic Agents

inferred← citeshttps://doi.org/10.3390/computation14090206openalex-snapshot

YOLO-Based Object Localization and Classification in UAV Images Compressed by JPEG

inferred← citeshttps://doi.org/10.3390/electronics15112247openalex-snapshot

OPTP-System: A Lightweight Pedestrian Trajectory Prediction System for Complex Occlusion Environments

inferred← citeshttps://doi.org/10.3390/sym17050724openalex-snapshot

You Only Look Once–Aluminum: A Detection Model for Complex Aluminum Surface Defects Based on Improved YOLOv8

inferred← citeshttps://doi.org/10.3390/w17142111openalex-snapshot

Intelligent Flood Scene Understanding Using Computer Vision-Based Multi-Object Tracking

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