DeepDiffusion: Unsupervised Learning of Retrieval-Adapted Representations via Diffusion-Based Ranking on Latent Feature Manifold

DeepDiffusion: Unsupervised Learning of Retrieval-Adapted Representations via Diffusion-Based Ranking on Latent Feature Manifold

Unsupervised learning of feature representations is a challenging yet important problem for analyzing a large collection of multimedia data that do not have semantic labels. Recently proposed neural network-based unsupervised learning approaches have succeeded in obtaining features appropriate for c...

Full description

Bibliographic Details
Main Authors: Takahiko Furuya, Ryutarou Ohbuchi
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Unsupervised representation learning
multimedia information retrieval
deep learning
Online Access:https://ieeexplore.ieee.org/document/9934898/

Similar Items

Similar Items