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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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

[Amélioration de la série YOLOv7/YOLOv5 NO.52] Intégration du module C2f dans YOLOv8

[Interprétation de l'article] ConvNeXt V2 : Co-designing and Scaling ConvNets with Masked Autoencoder

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)

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

CVPR 2023 | Le dernier backbone FasterNet

YOLOv5, v8 Problem mit der Anzeige chinesischer Etiketten

[Segmentation sémantique] DeepLab v3+ (DeepLab v3 Plus, Backbone, Xception, MobileNet v2, Encoder, Decoder, ASPP, fusion multi-échelle, convolution dilatée)

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

YOLOv5 - разрешение ошибки: UnicodeDecodeError: кодек utf-8 не может декодировать байт 0xb2 в позиции 6: invalidstartbyte

YOLOv5模型剪枝压缩(2)-YOLOv5模型简介和剪枝层选择

Mangez yolov8 bouchée par bouchée (2)

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

YOLOv5 a publié la version officielle v6.2

Вторая практика модификации сети YOLOv5 (v7.0): замена головки с одной ветвью на головку развязки с двумя ветвями YOLOX (DecoupleHead)

Améliorations de YOLOv5, YOLOv8 : transformateur BoTNet

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