Alleviating the Semantic Gap for Generalized fMRI-to-Image Reconstruction Tao Fang

Feb-9-2026, 17:55:48 GMT–Neural Information Processing Systems

CLIP model to map the training data to a compact feature representation, which essentially extends the sparse semantics of training data to dense ones, thus alleviating the semantic gap of the instances nearby known concepts (i.e., inside the

artificial intelligence, machine learning, natural language, (17 more...)

Neural Information Processing Systems

Feb-9-2026, 17:55:48 GMT

Conferences PDF

Add feedback

Country:
- Asia > China > Zhejiang Province > Hangzhou (0.04)

Industry:
- Health & Medicine
  - Health Care Technology (0.57)
  - Therapeutic Area > Neurology (0.69)

Technology:
- Information Technology
  - Artificial Intelligence
    - Machine Learning
      - Neural Networks (0.94)
      - Statistical Learning (0.68)
    - Natural Language (1.00)
    - Representation & Reasoning (1.00)
    - Vision (1.00)
  - Sensing and Signal Processing > Image Processing (1.00)

Duplicate Docs Excel Report

Title
Alleviating the Semantic Gap for Generalized fMRI-to-Image Reconstruction Tao Fang

Similar Docs Excel Report more

Title	Similarity	Source
None found