YOLOV5/YOLOV8 improvement: CVPR23: join the ConvNeXt V2 backbone, effectively increase points - Code World

YOLOV5/YOLOV8 improvement: CVPR23: join the ConvNeXt V2 backbone, effectively increase points

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Origin blog.csdn.net/m0_51530640/article/details/131126340

YOLOV5/YOLOV8 improvement: CVPR23: join the ConvNeXt V2 backbone, effectively increase points

YOLOV5/YOLOV8 improvement: CVPR23: join the ConvNeXt V2 backbone, effectively increase points

YOLOV5/YOLOV8 improvement: CVPR23: join the ConvNeXt V2 backbone, effectively increase points

YOLOV5/YOLOV8 improvement: CVPR23: join the ConvNeXt V2 backbone, effectively increase points

YOLOV5/YOLOV8 improvement: CVPR23: join the ConvNeXt V2 backbone, effectively increase points

YOLOV5/YOLOV8 improvement: CVPR23: join the ConvNeXt V2 backbone, effectively increase points

YOLOV8 improvement: CVPR 2023 | Add EMA attention mechanism in different positions of C2f module, effectively increase points

YOLOV8 improvement: add Wiseiou, effectively increase points

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

Третий метод модификации сети YOLOv5 (v7.0): замените головку с одной ветвью на основе якоря и головку на головку с двойной развязкой без якоря yolov8 (DecoupleHead от yolox)

YoloV8 improvement strategy: NWD new paradigm of small target detection, helping YoloV5 and V8 to violently increase their points on small targets

YOLOV8 improvement: CVPR2023: Join the EfficientViT backbone: memory efficient ViT with cascade group attention

[Mejora de la serie YOLOv7/YOLOv5 NO.52] Integración del módulo C2f en YOLOv8

Yolov8 improvement --- attention mechanism: ShuffleAttention, ECA, EffectiveSE, SE

YOLOv7 Backbone | Подробное объяснение исходного кода

Verbesserung der YOLO-Serie | YOLOv5/v7 ersetzt das Backbone-Netzwerk durch ResNet50/ResNet101

YoloV8 improvement strategy: SPD-Conv is added to YoloV8, allowing small targets to have nowhere to hide

YOLOV8 improvement: add the RepGhostBottleneck module in the C2f module, effectively increasing points

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

Проект 2: Используйте Yolov5 и deepsort для отслеживания транспортных средств и пешеходов, а также расчета скорости и ускорения цели в режиме реального времени (с функцией обнаружения превышения скорости)

Reproducción del backbone YoLoV5 basado en Pytorch (Parte 1)

[Interpretación del artículo] ConvNeXt V2: codiseño y escalado de ConvNets con codificador automático enmascarado

Target detection algorithm improvement series embedding Deformable ConvNets v2 (DCNv2)

Comer yolov8 bocado a bocado (2)

Mejoras de YOLOv5, YOLOv8: Transformador BoTNet

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

[Segmentación semántica] DeepLab v3+ (DeepLab v3 Plus, Backbone, Xception, MobileNet v2, codificador, decodificador, ASPP, fusión multiescala, convolución dilatada)

Yolov5 облегченный: CVPR2023｜RIFormer: минималистская архитектура ViT, которая может достичь производительности SOTA без TokenMixer

Улучшение YOLOv5: CVPR 2023 | SCConv: свертка пространственной и канальной реконструкции Plug-and-Play

YOLOv5模型剪枝压缩(2)-YOLOv5模型简介和剪枝层选择

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