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 - Code World

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

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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

[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.79] The improved loss function is VariFocal Loss

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.70] NonDeepNe (ParNet module), a lightweight attention mechanism that does not increase network depth

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)

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.85] Use TransformerDecoderHead in RT-DETR to improve yolov5

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

YOLOv5 improves the latest ICCV2023 conference LSKNet: the field of large selective convolution kernel is explored for the first time to help small target detection

YOLOv8's latest improvement series: YOLOv8+RepViT, re-examines mobile CNN from the perspective of ViT, effectively improving the model detection effect! ! ! 1.3ms delay-Tsinghua ICCV 2023 latest open source mobile network architecture RepViT

Target detection algorithm (R-CNN, fast R-CNN, faster R-CNN, yolo, SSD, yoloV2, yoloV3, yoloV4, yoloV5, yoloV6, yoloV7)

YOLOv8 latest improvement series: YOLOV8 backbone improvements - Huawei Noah proposes a new backbone architecture VanillaNet. YOLOv8 integrates the power of deep learning minimalism to greatly improve the robustness of the model! !

Detailed explanation of RepLKNet paper: 31×31 super large convolution kernel model

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

Tsinghua and Megvii proposed RepLKNet: a CNN network with a large kernel of 31×31, which has better performance than Swin

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

The latest overview of the YOLO series from YOLOv1 to YOLOv8 [April 2023]

CVPR 2022 | The convolution kernel is as large as 31x31! Ups and downs and efficient! Tsinghua & Megvii proposed RepLKNet: a new visual backbone network...

Python DeepLab series methods: a few pictures to understand ASPP, the upgraded version of hole convolution, the advantages of hole convolution

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

The first Yolov5/Yolov7 optimization: Adam should change! Stanford's latest Sophia optimizer, 2 times faster than Adam | Stanford's latest results in May 2023

Field smoke detection based on Yolov8 (4): Channel Priority Convolution Attention (CPCA), the effect is instantaneous to beat CBAM and SE, etc. | Latest publication of the Chinese Academy of Sciences in 2023

Improvements of YOLOv5 over YOLOv4

Improvements to YOLOv8

YOLOv5, YOLOv8 improvements-BIFPN

YOLOv5, YOLOv8 improvements: BoTNet Transformer

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