Hacker News
- Deep learning for visual question answering: demo with Keras code http://iamaaditya.github.io/2016/04/visual_question_answering_demo_notebook 17 comments
Linked pages
- A Word is Worth a Thousand Vectors | Stitch Fix Technology â Multithreaded http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-worth-a-thousand-vectors/ 13 comments
- GitHub - abhshkdz/neural-vqa: Visual Question Answering in Torch https://github.com/abhshkdz/neural-vqa 9 comments
- GloVe: Global Vectors for Word Representation http://nlp.stanford.edu/projects/glove/ 7 comments
- GitHub - avisingh599/visual-qa: [Reimplementation Antol et al 2015] Keras-based LSTM/CNN models for Visual Question Answering https://github.com/avisingh599/visual-qa 0 comments
- GitHub - GT-Vision-Lab/VQA_LSTM_CNN: Train a deeper LSTM and normalized CNN Visual Question Answering model. This current code can get 58.16 on OpenEnded and 63.09 on Multiple-Choice on test-standard. https://github.com/VT-vision-lab/VQA_LSTM_CNN 0 comments
Related searches:
Search whole site: site:iamaaditya.github.io
Search title: Visual Question Answering Demo in Python Notebook – Aaditya Prakash (Adi) – Machine Learning
See how to search.