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ASL Alphabet Detection and deploy model #336
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Can you please assign this to me |
Can i have this issue assigned. |
Hello, I'm eager to contribute to the ASL alphabet detection project using deep learning. Here's my proposed workflow: Data Exploration: Review existing ASL datasets to understand their quality and diversity. If necessary, augment data or collect additional samples to ensure robust training. Model Selection: Experiment with CNN architectures like ResNet or EfficientNet, optimizing for both accuracy and computational efficiency. Training Strategy: Implement techniques like transfer learning and data augmentation to train the model on the ASL dataset effectively. Evaluation Metrics: Define evaluation metrics such as accuracy, precision, and recall to measure model performance accurately. Hyperparameter Tuning: Fine-tune model hyperparameters using techniques like grid search or random search to optimize performance. Documentation: Maintain clear and concise documentation throughout the process, ensuring easy replication and future enhancements. Looking forward to diving in and collaborating with you! Best regards, |
can i have this? |
Assign this issue to me |
I’m interested in contributing to the ASL Alphabet Detection and Deployment Model project. This is an exciting opportunity to leverage computer vision techniques to enhance communication accessibility. Here’s my proposed plan: Data Collection: Utilize existing datasets or create a dataset of ASL hand signs for training the model. |
You can refer this dataset:
https://www.kaggle.com/grassknoted/asl-alphabet
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