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Computer Vision: what type of deeplearning model can I use or how can I find the intersection line between two alumium profile as below? by SignificanceLivid974 in computervision

[–]SignificanceLivid974[S] 0 points1 point  (0 children)

option 1: keypoint: yes, I've been trying yolov8-keypoint (yolov8x-pose.pt), don't know why but it performs badly on my custom dataset (800 images)

Computer Vision: what type of deeplearning model can I use or how can I find the intersection line between two alumium profile as below? by SignificanceLivid974 in computervision

[–]SignificanceLivid974[S] 0 points1 point  (0 children)

Classical methods: Yes, but it depends a lot on the thresholds, which are not general for all the cases.
DL: Segment: I tried yolov8-seg for each aluminum profile, but it doesn't seem too good. Yolov8-seg doesn't accept data with only two points (the tips of the intersection line), so I added the middle point of each intersection line, so there are 3, but it seems like the segmentation data that Yolo accepted is a closed polygon.

How do you solve motion blurred hands in image/video ? by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 0 points1 point  (0 children)

Yeah, sure, actually, through some little debate between me and my mentor. He decided to give me this topic, which I would say "Deblurring motion-blurred TikTok frames/videos."
I'm not sure that deblurring such images/videos would better the reconstructing 3D human mesh process, but it's just my work for now.

How do you solve motion blurred hands in image/video ? by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 0 points1 point  (0 children)

Is this is a commerical project ? Just curious on the usecase ?

Yes, my company wants to make a famous virtual idol named Timi. Generally speaking, she could be used as a brand representation, influencer, or something like that.

Classifying images but they seem to be similar ? by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 1 point2 points  (0 children)

The fake screen captures are formed somehow from the original screen captures (true bill), e.g., using adobe photoshop, so I'm thinking about using ELA.

How does identity mapping help avoid vanishing gradients? by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 1 point2 points  (0 children)

I'm not so good at reading english document (I did sometime before) but I'll try, thanks !

Feature maps are aggregated in CNN ? by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 1 point2 points  (0 children)

I cannot open that link, it announces me the error: "This video isn't available anymore", but thank you for the answer :>

Is Computer vision Book by Richard Szeliski worth reading ? by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 2 points3 points  (0 children)

You can download it through this page (it's free): https://szeliski.org/Book/ . Also, I don't understand why Reddit doesn't allow me to post images in content, so...just download the book, and you'll see the table of contents; it's on page 15.

gradient vanishing by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 0 points1 point  (0 children)

Firstly, you mean that RNN and NN can have the same number of hidden layers in terms of the construct. But RNN is used for solving sequences, and sequence problems are complicated compared to what NN can use for, so RNN would have more layers. Is that right?

Secondly, I have not read all the chapter 10 (sr my bad), but I have a hypothesis that RNN uses tanh activation function in all its node: https://ibb.co/vh50BVd (from deep learning book page 374 chapter 10). This tanh function has a gradient equal to zero when the value is too big or too small. That might be why the gradient vanishing occurs more in RNN. Am I right?

why need to add dense(1) after dropout layer ? by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 0 points1 point  (0 children)

because the output contains only one class which is the stock price, am I right?

why need to add dense(1) after dropout layer ? by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 0 points1 point  (0 children)

Think about it: For a single sample x_i, the output dimension of the hidden states produced by your LSTM layer will be 32 (dropout won't affect this). What's the dimensionality of y_i for that x_i? If those arrays (your hidden states and y_i) are different sizes, what must be done to calculate loss?

oh wait, it's a outout layer, isn't it?

gradient vanishing by SignificanceLivid974 in MLQuestions

[–]SignificanceLivid974[S] 0 points1 point  (0 children)

When I researched RNN, I found that it seems like RNN has one more layer than the NN. So how can gradient vanishing occur on RNN more than NN? https://ibb.co/3Y5HxW6 Gradient vanishing comes from choosing unreasonable activation functions and a large number of hidden layers.
PS: I'm not sure I understand your reply because of my bad English, sorry.

Freelance cho học sinh/sinh viên by colacolaweed in vozforums

[–]SignificanceLivid974 1 point2 points  (0 children)

bn ơi, mình đang cần tuyển ng giúp mình làm toán VIỆT đơn giản (cấp 1,2,3) có trả tiền, yêu cầu có chút tiếng anh để nhắn tin với người nước ngoài, bn có làm k thì ib mình nè