Multiple Mechanisms to Strengthen the Ability of YOLOv5s for Real-Time Identification of Vehicle Type
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Summary
This paper uses YOLOv5s as the backbone network to propose a large-scale convolutional fusion module called the ghost cross-stage partial network (G_CSP), which can integrate large- scale information from different feature maps to identify vehicles on the road.
- Type
- article
- Published
- 2022-08-18
- Cited by
- 12
- References
- 38
- Access
- Open access
- OpenAlex
- https://openalex.org/W4293790443
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:251701219
Keywords
Computer science, Pooling, Pyramid (geometry), Task (project management), Identification (biology)
References
- The Pascal Visual Object Classes (VOC) Challenge
- BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling
- Object Detection With Deep Learning: A Review
- CenterNet: Keypoint Triplets for Object Detection
- Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving
- CBAM: Convolutional Block Attention Module
- FCA-Net: Adversarial Learning for Skin Lesion Segmentation Based on Multi-Scale Features and Factorized Channel Attention
- Deep semantic segmentation of natural and medical images: a review
- GhostNet: More Features From Cheap Operations
- Recent Advances in Deep Learning for Object Detection
- Epileptic Seizure Detection in EEG Signals Using a Unified Temporal-Spectral Squeeze-and-Excitation Network
- Co-Optimizing Performance and Memory Footprint Via Integrated CPU/GPU Memory Management, an Implementation on Autonomous Driving Platform
- Multi-View Vehicle Detection Based on Fusion Part Model With Active Learning
- Packet Preprocessing in CNN-Based Network Intrusion Detection System
- Rotate to Attend: Convolutional Triplet Attention Module
- Object detection in real time based on improved single shot multi-box detector algorithm
- Vision Transformers for Remote Sensing Image Classification
- Robust Vehicle Detection in High-Resolution Aerial Images With Imbalanced Data
- MSB R-CNN: A Multi-Stage Balanced Defect Detection Network
- An All-in-One Vehicle Type and License Plate Recognition System Using YOLOv4
Cited by
- Traffic Light Detection and Recognition Method Based on YOLOv5s and AlexNet
- Research on deep learning garbage classification system based on fusion of image classification and object detection classification.
- MCS-YOLO: A Multiscale Object Detection Method for Autonomous Driving Road Environment Recognition
- An Energy-Saving Road-Lighting Control System Based on Improved YOLOv5s
- Road Scene Multi-Object Detection Algorithm Based on CMS-YOLO
- Driving Perception in Challenging Road Scenarios: An Empirical Study
- A Lightweight Vehicle Detection Method Fusing GSConv and Coordinate Attention Mechanism
- EDSD: efficient driving scenes detection based on Swin Transformer
- Algorithm for smoking detection based on upgraded YOLACT
- Lightweight container number recognition based on deep learning
- Detection of Interstitial Lung Disease Lesions in CT Images Based on YOLOv8-Seg and Atrous Spatial Pyramid Pooling
- HDCF-Mamba: Bridging Global Dependencies and Local Dynamics for Multi-Scale PV Forecasting
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