YOLOv8/YOLOv7/YOLOv5 Series Improvements | Directory List - コードワールド

YOLOv8/YOLOv7/YOLOv5 Series Improvements | Directory List

開発 2023-07-11 18:50:46 訪問数: null

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転載: blog.csdn.net/moonlightpeng/article/details/131635493

YOLOv8/YOLOv7/YOLOv5 Series Improvements | Directory List

YOLOv8/YOLOv7/YOLOv5 Series Improvements | Directory List

YOLOv8/YOLOv7/YOLOv5 Series Improvements | Directory List

YOLOv8/YOLOv7/YOLOv5 Series Improvements | Directory List

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.83] Change the backbone feature extraction network Backbone to RevCol

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.79] The improved loss function is VariFocal Loss

What improvements does YOLOv8 have over the previous generation?

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.70] NonDeepNe (ParNet module), a lightweight attention mechanism that does not increase network depth

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.84] are integrated into the 2023 latest large convolution kernel CNN architecture RepLKNet upgraded version-UniRepLKNet

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.80] introduce plug-and-play CloFormer: the perfect integration of attention mechanism and convolution

YOLOv5 improvements | Main article | CSWinTransformer cross-shaped window network improved feature fusion layer

YOLOv5 improvements | 2023 attention | EMAttention attention mechanism (with multiple positions that can be added)

YOLOV5 adds attention mechanism, taking ECAttention as an example (series)

YOLOv5 YOLOv7 YOLOv8 のモデルテストの比較と結論

YOLOv5、YOLOv8 の改善-BIFPN

YOLOv5, YOLOv8 improvements-BIFPN

YOLOv5, YOLOv8 improvements: BoTNet Transformer

Nanny level tutorial - YOLO series (YOLOv5/YOLOv7/YOLOv8) algorithm training data set

[YOLOv7/YOLOv5 series improvement NO.52] Integrating the C2f module in YOLOv8

YOLOv8 and its improvements (2) This article (45,000 words) | Training self-built target detection and image segmentation data set |

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn系アルゴリズム改良【NO.66】回転対象枠検出に改良

YOLOv8 の使用方法の紹介と YOLOv7、YOLOv6、YOLOv5 のパフォーマンスの比較

Improvements to YOLOv8

【YOLOv7/YOLOv5シリーズ改善NO.52】C2fモジュールをYOLOv8に統合

ビデオターゲット検出 yolo アルゴリズム小規模モデル自己学習モデルの比較 (yolov5 yolov7 yolov8)

Artifact with rising points: CVPR2023 InceptionNeXt. When Inception meets ConvNeXt, plug and play in Yolov5/Yolov7/Yolov8, small target detection has obvious points.

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.67] Add attention mechanism MHSA

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

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.72] attention mechanism Linear Context Transform Block (LCT module)

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.73] Adding asymptotic feature pyramid network (AFPN module)

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