1.learn the framework of yolo-v8

2. learn the seam attention mechanism（https://arxiv.org/abs/2208.02019）

3. Try to come up with a better data fusion framework

4.Evaluation mechanisms are learning

1. Finish paper "Corn plant phenotypic parameters extraction algorithm based on keypoint detection and stereo images"
2. Change my paper "FCOS_Stereo"

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The first draft of the paper has been completed, and it is expected to be completed in one week

1. detect key points based on yolo-pose
2. use mpdiou and focal mechanism to improve accuracy
3. Use GSCONV and pruning framework to reduce the parameters of the model

I am writing my paper and expect to finish the first draft within a week.

1.update my flow

2.As what i do in the last work,using internal parameters to project the key point to make data.

3.Adding the stereo -> depth netwotk to obtain the depth map

The pruning frame has a BUG in the library, hard to make progress.

Ⅰ.learn the different varities of the IoU:

1.GIoU：https://openaccess.thecvf.com/content_CVPR_2019/html/Rezatofighi_Generalized_Intersection_Over_Union_A_Metric_and_a_Loss_for_CVPR_2019_paper.html

2.DIoU:

https://ojs.aaai.org/index.php/AAAI/article/view/6999

3.CIoU：

https://ieeexplore.ieee.org/abstract/document/9520717

4.MPDIoU：

1.revise my SNPD paper

2. The characteristic values of corn key points were calculated

1. revise my SNPD paper to BOOK
2. Take more photos of the corn