from typing import Tuple, List, Dict
import datetime
class ChenKaiXu:
pass
class Attributes(ChenKaiXu):
@property
def contact(self) -> Tuple[str, str, str]:
email = "chenkaixusan@gmail.com"
google_scholar = "https://scholar.google.com/citations?user=kpNboagAAAAJ"
blog = "https://chenkaixusan.github.io/blog/"
linkedin = "https://www.linkedin.com/in/chenkaixusan/"
return email, google_scholar, blog, linkedin
@property
def life(self) -> Tuple[List[str], int]:
langs = ['Chinese', 'English', 'Japanese']
age = datatime.datetime.now().year - 1996
return langs, age
@property
def coding(self) -> Tuple[Dict[str, List[str]], List[str], List[str], Dict[str]]:
langs = {
'expert' : ['python'],
'intermediate': ['jave', 'c++'],
'learning' : ['c', 'c#', 'php']
}
specialities = ['AI application engineering', 'web/app development']
research topic = ['AI', 'health care', 'deep learning']
ide = ['vscode']
pc = {
'MacOS': {
'macmini m1': {
'processor': 'm1 | 8 cores',
'ram' : '16gb',
'gpu' : 'm1 | 8 cores'
},
'macbook pro': {
'processor': 'm5 | 10 cores',
'ram' : '24gb',
'gpu' : 'm5 | 10 cores'
},
'Windows': {
'custom': {
'OS' : 'Windows 11',
'processor': 'AMD ryzen 7 5700X | 8 cores',
'ram' : '64gb 2400',
'gpu' : 'nvidia 3080'
}
}
}
return langs, specialities, research topic, ide, pc
-
Tsukuba University
- Japan
-
05:54
(UTC +09:00) - chenkaixusan.github.io/blog/
- https://orcid.org/0009-0003-8698-8899
- in/chenkaixusan
- https://scholar.google.com/citations?user=kpNboagAAAAJ
Highlights
- Pro
Pinned Loading
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deep-learning-project-template
deep-learning-project-template Public templateForked from Lightning-AI/deep-learning-project-template
Pytorch Lightning code guideline for conferences
Python
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Walk_Video_PyTorch
Walk_Video_PyTorch Public archiveA classification task for a walk video task, based on PyTorch and PyTorch Lightning.
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DEMT-LI
DEMT-LI PublicForked from nadeemlab/SeqX2Y
Sequence-to-sequence image and contour prediction library for lung dataset, with PyTorch.
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Skeleton_ASD_PyTorch
Skeleton_ASD_PyTorch Public archivePhaseMix: A Periodic Motion Fusion Method for Adult Spinal Deformity Classification, based on PyTorch.
Jupyter Notebook 1
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Temp_Feedback
Temp_Feedback PublicThis project use the ML&DL method to feed back the predict temputre to the backend.
Jupyter Notebook
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