Generating FER models using ChatGPT

Abstract

This paper investigates the utilisation of ChatGPT (Generative Pre-trained Transformer) in the field of Facial Emotion Recognition (FER), streamlining development processes and making them smoother and faster. With ChatGPT, coding and debugging happen fast, leading to the swift creation of performing models in mere minutes. It highlights the transformative potential of integrating ChatGPT into image processing workflows, accelerating progress in computer vision, graphics, and multimedia. This paper also shows the importance of word choice and developer skill in finding the right balance between speed and accuracy. It sets the stage for further investigations into advanced Large Language Models (LLMs) and finetuning parameters, leading towards faster, more efficient image processing techniques.

Keywords

• facial emotion recognition (fer)
• deep neural networks
• convolutional neural networks (cnn)
• computer vision
• machine learning
• large language model (llm)
• chatgpt(generative pretrained transformer)