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image-descriptions

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In this project, we use a Deep Recurrent Architecture, which uses CNN (VGG-16 Net) pretrained on ImageNet to extract 4096-Dimensional image feature Vector and an LSTM which generates a caption from these feature vectors.

  • Updated Sep 9, 2020
  • Jupyter Notebook

NL Generation from structured inputs. Focuses on generating natural language descriptions for images by exploring the relationship between textual descriptions and image attributes. Leveraging an encoder-decoder architecture with LSTM cells, the system transforms normalized vector representations of attributes into fixed-length vector.

  • Updated Jan 7, 2024
  • Jupyter Notebook

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