Gain point artifact: small target performance improvement based on Yolov5/Yolov7 - Code World

Gain point artifact: small target performance improvement based on Yolov5/Yolov7

Enterprise 2023-06-04 22:19:21 views: null

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Origin blog.csdn.net/m0_63774211/article/details/130866699

Gain point artifact: small target performance improvement based on Yolov5/Yolov7

Introduction of Yolov5 small target performance improvement solution

Yolov5/Yolov7 improvement---attention mechanism: ICASSP2023 EMA is based on efficient multi-scale attention of cross-space learning, the effect is better than ECA, CBAM, CA | small target rises significantly

YOLOv5 Improvement Series (20) - Add BiFormer Attention Mechanism (CVPR2023|Small Goal Increase Point Artifact)

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.69] Improvement of small targets in remote sensing image target detection CATnet (ContextAggregation module)

YOLOv7 Improvement 22: Raising Point Artifact - Introducing Recursive Gated Convolution (gnConv)

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

YOLOv5 improvement: Introduce DenseNet idea to create dense connection module, completely improve target detection performance

[YOLOv7/YOLOv5 series improvement NO.53] Integrating the ECVBlock module in the CFPNet network to improve the detection ability of small targets

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

Development and construction of infrared high-altitude small target detection and recognition analysis system based on YOLOv7

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

The first release of Yolov5/Yolov7 point increase artifact: Huawei Noah 2023's minimalist neural network model VanillaNet---VanillaBlock helps detection and achieves violent point increase

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

[Reading notes for target detection papers] Small-object detection based on YOLOv5 in autonomous driving systems

Video target detection yolo algorithm small model self-training model comparison (yolov5 yolov7 yolov8)

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

Data enhancement: Based on Yolov5/Yolov7/Yolov8---automatically generate pictures and xml files to solve problems such as difficult training of small samples

YOLOv8’s latest improvement series: Optimize CIoU to Wise-IoU to help improve detection performance and effectively improve small target detection accuracy! ! ! Far ahead! ! ! ! !

[YOLOv7/YOLOv5 series algorithm improvement NO.7] Loss function improvement

YOLOV5/YOLOV7/YOLOV8 Improvement Column

YOLOv8 use introduction and YOLOv7, YOLOv6, YOLOv5 performance comparison

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

YOLOv7 algorithm reconstruction: personal self-improvement, as simple as YOLOv5, only 31 layers

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

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

100 practical application cases of target detection YOLO - small target detection based on improved YOLOv8 (continued)

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

yolov3 yolov4 yolov5 yolov6 yolov7 yolov8 yolox Algorithm improvement, algorithm customization, algorithm guidance

yolov7 improvement series

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