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Small Object Detection Network Based on Attention Mechanism and Feature Fusion

https://doi.org/10.2139/ssrn.4876039
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inferredcites →https://doi.org/10.1002/int.22654openalex-extracted
Dual‐branch mutual assistance network for salient object detection
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_1openalex-extracted
CBAM: Convolutional Block Attention Module
inferredcites →https://doi.org/10.1007/978-3-030-92307-5_45openalex-extracted
Task-Driven Super Resolution: Object Detection in Low-Resolution Images
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-extracted
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1016/j.engappai.2022.105504openalex-extracted
BANet: Small and multi-object detection with a bidirectional attention network for traffic scenes
inferredcites →https://doi.org/10.1016/j.engappai.2023.107139openalex-extracted
Dual Cross-Attention for medical image segmentation
inferredcites →https://doi.org/10.1016/j.imavis.2020.103910openalex-extracted
Recent advances in small object detection based on deep learning: A review
inferredcites →https://doi.org/10.1016/j.jvcir.2023.103752openalex-extracted
FE-YOLOv5: Feature enhancement network based on YOLOv5 for small object detection
inferredcites →https://doi.org/10.1109/access.2020.3046515openalex-extracted
YOLO-ACN: Focusing on Small Target and Occluded Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2014.81openalex-extracted
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-extracted
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-extracted
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.690openalex-extracted
YOLO9000: Better, Faster, Stronger
inferredcites →https://doi.org/10.1109/cvpr.2018.00913openalex-extracted
Path Aggregation Network for Instance Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2019.00075openalex-extracted
Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01079openalex-extracted
EfficientDet: Scalable and Efficient Object Detection
inferredcites →https://doi.org/10.1109/iccv.1995.466933openalex-extracted
Proceedings of IEEE International Conference on Computer Vision
inferredcites →https://doi.org/10.1109/iccv.2017.324openalex-extracted
Focal Loss for Dense Object Detection
inferredcites →https://doi.org/10.1109/iccv.2019.00972openalex-extracted
FCOS: Fully Convolutional One-Stage Object Detection
inferredcites →https://doi.org/10.1109/jproc.2023.3238524openalex-extracted
Object Detection in 20 Years: A Survey
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-extracted
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1109/tpami.2018.2858826openalex-extracted
Focal Loss for Dense Object Detection
inferredcites →https://doi.org/10.1109/tpami.2019.2913372openalex-extracted
Squeeze-and-Excitation Networks
inferredcites →https://doi.org/10.1109/tpami.2021.3119563openalex-extracted
Detection and Tracking Meet Drones Challenge
inferredcites →https://doi.org/10.1109/tsmc.2020.3005231openalex-extracted
A Survey of the Four Pillars for Small Object Detection: Multiscale Representation, Contextual Information, Super-Resolution, and Region Proposal
inferredcites →https://doi.org/10.1145/3402666openalex-extracted
Correlation Discrepancy Insight Network for Video Re-identification
inferredcites →https://doi.org/10.1155/2020/7845384openalex-extracted
CenterFace: Joint Face Detection and Alignment Using Face as Point
inferredcites →https://doi.org/10.1155/2022/8684138openalex-extracted
A Deep Learning‐Based Semantic Segmentation Architecture for Autonomous Driving Applications
inferredcites →https://doi.org/10.1155/2023/6266209openalex-extracted
ALFPN: Adaptive Learning Feature Pyramid Network for Small Object Detection
inferredcites →https://doi.org/10.3390/app9204396openalex-extracted
Machine Learning and Deep Learning Methods for Intrusion Detection Systems: A Survey
inferredcites →https://doi.org/10.48550/arxiv.1511.06434openalex-extracted
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1804.02767openalex-extracted
YOLOv3: An Incremental Improvement
inferredcites →https://doi.org/10.48550/arxiv.2004.10934openalex-extracted
YOLOv4: Optimal Speed and Accuracy of Object Detection
inferredcites →https://doi.org/10.48550/arxiv.2112.05561openalex-extracted
Global Attention Mechanism: Retain Information to Enhance Channel-Spatial Interactions
inferredcites →https://doi.org/10.5121/csit.2019.91713openalex-extracted
Augmentation for small object detection
inferredcites →https://doi.org/10.4230/oasics.ng-res.2024.2openalex-snapshot
A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control (Invited Paper)
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