Artificial Intelligence
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generate a flowchart for vqa


[insert image here] 1. Start: The VQA (Visual Question Answering) system is initialized. 2. Get Image and Question: The system receives an image and a question about the image. 3. Process Image: The image is processed using a pre-trained CNN (Convolutional Neural Network) to extract visual features. 4. Process Question: The question is processed using an NLP (Natural Language Processing) model to convert it into a numerical representation. 5. Combine Features: The visual and textual features are combined to create a joint representation of the image and question. 6. Send to Model: The joint representation is sent to a pre-trained VQA model for prediction. 7. Predict Answer: The VQA model outputs a predicted answer to the question. 8. Is Answer Confident? The system checks if the predicted answer has a high confidence score. 9. Yes: If the confidence score is high, the predicted answer is selected as the final answer to the question. 10. No: If the confidence score is low, the system prompts the user for clarification or additional information. 11. Provide Answer: The final answer is provided to the user, either the predicted answer or the clarified answer. 12. End: The VQA system ends here.