@saikhantnaing62: ဘာလို့ငါယဖတွေပဲဖစ်နေရတာလဲး ကွာ😭 ငါမှကြည့်ရင်နဲ့ငိုပါငိုချင်တယ် မျက်ရေပါဝဲးတယ်ကွာ#ဒီချိန်တင်တော့viewတက်ပမလာ #fypシ゚ #ဒီတစ်ပုဒ်တော့fypပေါ်ရောက်ချင်တယ် #vdတွေရှယ်ကျ

င စိုင်း
င စိုင်း"💐
Open In TikTok:
Region: MM
Friday 08 May 2026 17:43:05 GMT
138624
15639
407
735

Music

Download

Comments

tses66
✎မလေးရှားနွားမ🐮 :
တကယ်ချစ်ရင်သန်မာပါတယ်ဆိုတဲ့ယောကျာ်းတွေလဲပြိုလဲရတာပဲ🥺
2026-05-09 02:41:48
303
zin.wai.naing24
😡 Zin ®™©😡 :
ဘယ်လိုဖစ်တာလဲ နောက်တစ်ယောက်တွဲသွားတာလား🥺🥺
2026-05-18 11:26:24
19
moji.soo
🎀 babe 🎀 :
ကြည့်နေရင်နဲ့ညီမမျက်ရည့်မဝယ်🥺
2026-05-27 15:46:14
1
kora8.0
Shower🫂 :
သီ ချင်းကြီး မထည့်ပါနဲ့လား ဘာမှမကြားရဘူး
2026-05-24 09:54:45
7
thet.phyo.han0s
T"s :
ဘယ်လိုဖစ်တာလဲရှင်းပြပါလား🥺
2026-05-09 16:44:41
10
aungzin1719gmail.com
👻Àűñĝ Žîñ Ĥțóó👻😏 :
broကျွန်တော်လဲအဲ့လိုခံစားရဘူးတယ်ဗျာ🥺🥺🥺
2026-06-09 21:33:06
1
obit940
T.H.Z :
2026-05-24 02:11:58
1
reece.2k90
@Zanny_ :
2026-05-09 16:34:03
2
thmthm202639.com2
THM :
ဟာကွာငါနဲ့တူတယ် ငါလဲခံစာဘူးခဲ့တယ် 😔🥀💔
2026-05-28 10:45:37
1
fa.yd7
Fa Yd :
ဟာဗျာကျွန်တော်ဆိုသူမစာမပို့တာ3နှစ်ရ ှိပြီဗျာနော်တော်ပို့နေသေ့တယ်ဗျာ🥺😞😞😞😞😞😞သူကိုလွမ်းနေတာ
2026-06-04 18:31:41
1
user729163767
Ko Kyaw :
စိတ်ကျပါတာရိး
2026-05-30 07:14:09
1
aungthankyaw2010
V͇̿I͇̿P͇̿8/Aung Than Kyaw :
2026-05-10 16:26:57
1
To see more videos from user @saikhantnaing62, please go to the Tikwm homepage.

Other Videos

Explore the implementation of Active Shape Models (ASM) for facial recognition using Python. This technical overview covers key concepts including shape representation, alignment, PCA, and model fitting. Discover how ASMs can be applied to face detection and expression analysis, along with their limitations and future directions. #ComputerVision #FaceRecognition #Python #MachineLearning #ImageProcessing #STEM #DataScience You can find, for free, this and all others slideshow on the xbe.at website Suggestions to reinforce your understanding of Active Shape Models: Implement each component: Build small Python scripts for each ASM step (landmark detection, shape alignment, PCA, etc.). This hands-on approach will deepen your understanding of the underlying mathematics and algorithms. Experiment with different datasets: Try applying your ASM implementation to various face datasets. This will help you understand how the model performs under different conditions and identify its strengths and weaknesses. Visualize intermediate results: Create visualizations for each stage of the ASM process. This can help you intuitively grasp how the model is working and where improvements might be needed. Compare with other methods: Implement alternative face recognition techniques (e.g., Eigenfaces, Fisherfaces) and compare their performance with ASMs. This comparative analysis will give you a broader perspective on facial recognition algorithms. Stay updated with recent research: The field of computer vision is rapidly evolving. Regularly read recent papers on facial recognition and try to incorporate new ideas into your ASM implementation. This will keep your skills sharp and your knowledge current.
Explore the implementation of Active Shape Models (ASM) for facial recognition using Python. This technical overview covers key concepts including shape representation, alignment, PCA, and model fitting. Discover how ASMs can be applied to face detection and expression analysis, along with their limitations and future directions. #ComputerVision #FaceRecognition #Python #MachineLearning #ImageProcessing #STEM #DataScience You can find, for free, this and all others slideshow on the xbe.at website Suggestions to reinforce your understanding of Active Shape Models: Implement each component: Build small Python scripts for each ASM step (landmark detection, shape alignment, PCA, etc.). This hands-on approach will deepen your understanding of the underlying mathematics and algorithms. Experiment with different datasets: Try applying your ASM implementation to various face datasets. This will help you understand how the model performs under different conditions and identify its strengths and weaknesses. Visualize intermediate results: Create visualizations for each stage of the ASM process. This can help you intuitively grasp how the model is working and where improvements might be needed. Compare with other methods: Implement alternative face recognition techniques (e.g., Eigenfaces, Fisherfaces) and compare their performance with ASMs. This comparative analysis will give you a broader perspective on facial recognition algorithms. Stay updated with recent research: The field of computer vision is rapidly evolving. Regularly read recent papers on facial recognition and try to incorporate new ideas into your ASM implementation. This will keep your skills sharp and your knowledge current.

About