YOLOv5/YOLOv8 verbesserte praktische Experimente: Original neue *** Subpixel-Faltung *** optimierte Upsampling-Technologie zur Verbesserung des Zielerkennungseffekts (Plug and Play) - Code World

YOLOv5/YOLOv8 verbesserte praktische Experimente: Original neue * Subpixel-Faltung * optimierte Upsampling-Technologie zur Verbesserung des Zielerkennungseffekts (Plug and Play)

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Origin blog.csdn.net/qq_44224801/article/details/131670316

YOLOv5/YOLOv8 verbesserte praktische Experimente: Original neue *** Subpixel-Faltung *** optimierte Upsampling-Technologie zur Verbesserung des Zielerkennungseffekts (Plug and Play)

YOLOv5/YOLOv8 verbesserte praktische Experimente: Original neue *** Subpixel-Faltung *** optimierte Upsampling-Technologie zur Verbesserung des Zielerkennungseffekts (Plug and Play)

YOLOv5/YOLOv8 verbesserte praktische Experimente: Original neue *** Subpixel-Faltung *** optimierte Upsampling-Technologie zur Verbesserung des Zielerkennungseffekts (Plug and Play)

YOLOv5/YOLOv8 verbesserte praktische Experimente: Original neue *** Subpixel-Faltung *** optimierte Upsampling-Technologie zur Verbesserung des Zielerkennungseffekts (Plug and Play)

Praktische Verbesserung von YOLOv8 | PoolFormer zum Ersetzen des Backbone-Netzwerks Backbone

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

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

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

Улучшение YOLOV8: CVPR 2023 | SCConv: свертка пространственной и канальной реконструкции Plug-and-Play

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

Verbesserte YOLOv8-Netzwerkarchitektur | Verwendung des SwinTransformer-Netzwerks | Verwendung von Verschiebungsfenstern zur Erzielung einer visuellen Transformation | Computer Vision

YOLOv5 / YOLOv8 experimentos práticos aprimorados: novo original *** convolução de subpixel *** tecnologia de upsampling otimizada para melhorar o efeito de detecção de alvo (plug and play)

Improved YOLOv8 | Plug and Play | Full-Dimensional Dynamic Convolution | "OMNI-DIMENSIONAL DYNAMIC CONVOLUTION"

YOLOV8 improvements: TripletAttention | plug-and-play lightweight attention mechanism

YOLOV8-Verbesserung: CVPR 2023 | SCConv: Plug-and-Play-Faltung zur räumlichen und Kanalrekonstruktion

YOLOV8-Verbesserung: CVPR 2023 | SCConv: Plug-and-Play-Faltung zur räumlichen und Kanalrekonstruktion

YOLOV8-Verbesserung: CVPR 2023 | SCConv: Plug-and-Play-Faltung zur räumlichen und Kanalrekonstruktion

YOLOV8-Verbesserung: CVPR 2023 | SCConv: Plug-and-Play-Faltung zur räumlichen und Kanalrekonstruktion

Video plug-in to play m3u8 format video (save original)

DRConv dynamic region-aware convolution based on Yolov5/Yolov7, plug and play, with significant growth!

Improve YOLOv8 | Plug and Play | YOLOv8 applies Slim-neck, a better neck design paradigm | "Slim-neck by GSConv: A Better Design Paradigm for Autonomous Vehicle Detector Architecture"

Attention mechanism: based on Yolov8's Triplet attention module, plug and play, the effect is better than cbam and se, and the increase point is obvious

YoloV8 rising point artifact: CFPNet-ECVBlock's small target detection, plug and play, helping to detect rising points

Verbesserung von YOLOv8 | Upgrade des Backbone-Netzwerks | YOLOv8-Backbone-Netzwerk ersetzt durch MobileNetV3 | Computer Vision

Improve YOLOv8 | Plug and Play | Add [SE] [CBAM] [ECA] [CA] attention mechanism in the C2F module | Attach a detailed structure diagram

Improve YOLOv8 | Plug and Play | Add [SimAM] [CoTAttention] [SKAttention] [Double Attention] attention mechanism in the C2F module | Attach a detailed structure diagram

Anweisungen zur Verwendung des Architektur-Plug-Ins mithilfe der Reflection-Technologie in PHP

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

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!

CFPNet based on YoloV5---ECVBlock's small target detection, plug and play, helping to detect rising points

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