YoloV5 improvement strategy: AAAI 2024 latest axial attention | Plug and play, the first choice for improvement | First launched on the entire network, including data sets and codes, ready to use out of the box! - Code World

YoloV5 improvement strategy: AAAI 2024 latest axial attention | Plug and play, the first choice for improvement | First launched on the entire network, including data sets and codes, ready to use out of the box!

Enterprise 2024-01-08 21:32:55 views: null

NoSuchKey

Guess you like

Origin blog.csdn.net/m0_47867638/article/details/135322613

YoloV5 improvement strategy: AAAI 2024 latest axial attention | Plug and play, the first choice for improvement | First launched on the entire network, including data sets and codes, ready to use out of the box!

YoloV5 improvement strategy: Frequency domain multi-axis representation learning module | First release on the entire network | Efficient increase points | Detailed code comments

YoloV8 improvement strategy: FastVit and YoloV8 are perfectly integrated, and the YoloV8 network is reconstructed with heavy parameters (first release on the entire network)

YoloV7 improvement strategy: Frequency domain multi-axis representation learning module | First release on the entire network | High-efficiency increase points | Detailed code comments

Improving YOLOv5/YOLOv8: Reproduction combined with plug-and-play | Efficient multi-scale attention (EMA), the module becomes a small helper for YOLOv5 improvement

daima8 resource network entire site data packaging complete code (integrated ripro9.1 theme, ready to use out of the box)

Ready to use right out of the box! HashData cloud data warehouse launched on Huawei Blue Whale App Store

[YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement NO.65] CVPR 2023 | Tsinghua team's plug-and-play network architecture—Slide-Transformer

Reproduce the latest MPDIoU improvement of YOLOv5: effective and accurate bounding box regression loss, defeating G/E/CIoU, the effect is obvious! ! !

Scrapy sets breadth first, crawls the latest data

YOLOv5 Improvement Series (21) - RepViT to replace the backbone network (Tsinghua ICCV 2023|The latest open source mobile terminal ViT)

YOLOv5 Improvement | 2023 Attention Chapter | iRMB Inverted Residual Block Attention Mechanism (Lightweight Attention Mechanism)

YoloV8 improvement strategy: Based on hierarchical attention FasterViT, let YoloV8 achieve a leap in performance

YOLOv8 improvements | Main article | The latest results in December TransNeXt feature extraction network (first release on the entire network)

YOLOv5, v7 improvement twenty-eight: ICLR 2022 rising point artifact - plug-and-play dynamic convolution ODConv

Yolov5/Yolov7 improvement --- attention mechanism: ShuffleAttention, ECA, EffectiveSE, SE

The first discussion - clear and specific improvement ideas

YOLOv5 Improvement Series (23) - MobileViTv2 to replace the backbone network (an efficient separable self-attention mechanism for mobile vision Transformer)

YOLOv7 Improvement: CVPR 2023 | SCConv: Plug-and-Play Convolution for Spatial and Channel Reconstruction

Yolov5/Yolov7 improvement --- attention mechanism: Polarized Self-Attention, the effect spikes CBAM, SE

Use yolov5 to train your own data set (suitable for Xiaobai's first training data set)

Practical improvement of YOLOv8 | Replacing the backbone network Backbone (5) Lightweight 2023 latest network VanillaNet, the power of minimalism in deep learning

YoloV8 improvement strategy: BAM bottleneck attention module | BAM detailed explanation and code comments | CBAM companion article | Effective points

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.71] attention mechanism Expectation-Maximization Attention (EMA module)

axial attention axial attention

Yolov5/Yolov7 improvement --- attention mechanism: SimAM (no parameter Attention) and NAM (based on standardized attention module), the effect spikes CBAM, SE

YOLOv6 Pro | Use the yaml file format to build a YOLOv6L network structure tutorial step by step (1) - the main network article, you can understand it at a glance, and share it with pure white dry goods (also applicable to the official YOLOv5 improvement)

Reproduce the latest MPDIoU improvement of YOLOv8: effective and accurate bounding box regression loss, defeating G/E/CIoU, the effect is obvious! ! !

YOLOV5 improvement: CVPR 2023 | Add EMA attention mechanism in different positions of C3 block, effectively increase points

YOLOV5 improvement: CVPR2023: join the EfficientViT backbone: memory access efficient ViT with cascade group attention

Recommended

Ranking

SpringBoot open source micro-channel ordering system! Comprehensive use projects, worth a visit!

hdu 6852Path6 (minimum cut shortest +)

Install sql server cluster

weblogic TypeError: unsupported operand type(s) for

The most complete macos installation xgboost tutorial in history

MySQL database slow query log configuration and analysis

The pit of script in the javaagent parameter of Btrace

Cloud management of enterprise storage management

Uncaught TypeError: str.replace is not a function

Pass 7230X Exam Using 7230X Exam Cram

Daily

More

2025-01-29(0)

2025-01-28(0)

2025-01-27(0)

2025-01-26(0)

2025-01-25(0)

2025-01-24(0)

2025-01-23(0)

2025-01-22(0)

2025-01-21(0)

2025-01-20(0)