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UTA Real-Life Drowsiness Dataset Analysis using DL

Open abhisheks008 opened this issue 1 year ago • 10 comments

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : UTA Real-Life Drowsiness Dataset Analysis using DL :red_circle: Aim : The aim is to analyze the dataset using Deep Learning methods and models, and also find out the best fitted model for this dataset. :red_circle: Dataset : https://www.kaggle.com/datasets/mathiasviborg/uta-rldd-fold5 :red_circle: Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.


📍 Follow the Guidelines to Contribute in the Project :

  • You need to create a separate folder named as the Project Title.
  • Inside that folder, there will be four main components.
    • Images - To store the required images.
    • Dataset - To store the dataset or, information/source about the dataset.
    • Model - To store the machine learning model you've created using the dataset.
    • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
  • Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

:red_circle::yellow_circle: Points to Note :

  • The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
  • "Issue Title" and "PR Title should be the same. Include issue number along with it.
  • Follow Contributing Guidelines & Code of Conduct before start Contributing.

:white_check_mark: To be Mentioned while taking the issue :

  • Full name :
  • GitHub Profile Link :
  • Email ID :
  • Participant ID (if applicable):
  • Approach for this Project :
  • What is your participant role? (Mention the Open Source program)

Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

abhisheks008 avatar May 05 '24 04:05 abhisheks008

Hi , I'm excited to contribute to this project. Could you please assign me? Looking forward to getting started! @abhisheks008

Full name : Tushti Thakur GitHub Profile Link : https://github.com/tushtithakur Email ID : [email protected] Approach for this Project : Implement different deep learning algorithms using the dataset, evaluate it and compare performance. What is your participant role? GSSoC 2024

tushtithakur avatar May 10 '24 06:05 tushtithakur

Hi @tushtithakur wait for the induction session to complete by today evening, after that issues will be assigned to the contributors.

abhisheks008 avatar May 10 '24 07:05 abhisheks008

@abhisheks008 Sure sir, I'll wait for the induction session to be completed. Thank you for the update!

tushtithakur avatar May 10 '24 12:05 tushtithakur

Hi @abhisheks008, Could you please assign this project to me?

Full name : Lalan Kumar GitHub Profile Link : https://github.com/kumar8074 Email ID : [email protected] Approach for this Project : Since it is a image processing project, First i'll try some of my own DL algorithms and also after that i can also utilise existing algorithms using Transfer Learning technique and try to bring out the most accuracte and efficient model. What is your participant role? GSSoC'24

kumar8074 avatar May 11 '24 15:05 kumar8074

also @abhisheks008 can you please add level to the project

kumar8074 avatar May 11 '24 15:05 kumar8074

Initially all the deep learning issues are of level 2. But it depends on the coontribution made by the contributors, if your contribution looks too good to us, I'll upgrade the label from level 2 to level 3. As this is an event where every contributor is getting points for their precious contributions and efforts and as an open source enthusiast I know how much time and effort it takes to make a complete deep learning project. That's why I follow this label upgradation through out my open source journey.

abhisheks008 avatar May 11 '24 15:05 abhisheks008

HI @abhisheks008 can you assign me this issue. The procedure I would be following is 1.Explore dataset. 2. Extract frames from the video. 3. perform preprocessing. 4. Try using different light weigh models to achieve real time detection (custom CNN, Yolo, MobileNet). 5. fine tune the model which gives the best accuracy.

Rohith766 avatar May 30 '24 13:05 Rohith766

✅ To be Mentioned while taking the issue :

Full name : GitHub Profile Link : Email ID : Participant ID (if applicable): Approach for this Project : What is your participant role? (Mention the Open Source program)

@Rohith766 can you mention your details like this

abhisheks008 avatar May 31 '24 04:05 abhisheks008

HI @abhisheks008 can you assign me this issue. Full name : Rohith Govindaraju GitHub Profile Link : https://github.com/Rohith766 Email ID : [email protected] Participant ID (if applicable): discord: manofinfinity_ Approach for this Project : 1.Explore dataset. 2. Extract frames from the video. 3. perform preprocessing. 4. Try using different light weigh models to achieve real time detection (custom CNN, Yolo, MobileNet). 5. fine tune the model which gives the best accuracy. What is your participant role? Gssoc'24 Contributor

Rohith766 avatar May 31 '24 04:05 Rohith766

Assigned @Rohith766

abhisheks008 avatar Jun 01 '24 02:06 abhisheks008