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pro vyhledávání: '"Barthel, Kai"'
Contrastive Language and Image Pairing (CLIP), a transformative method in multimedia retrieval, typically trains two neural networks concurrently to generate joint embeddings for text and image pairs. However, when applied directly, these models ofte
Externí odkaz:
http://arxiv.org/abs/2409.01936
For approximate nearest neighbor search, graph-based algorithms have shown to offer the best trade-off between accuracy and search time. We propose the Dynamic Exploration Graph (DEG) which significantly outperforms existing algorithms in terms of se
Externí odkaz:
http://arxiv.org/abs/2307.10479
Images sorted by similarity enables more images to be viewed simultaneously, and can be very useful for stock photo agencies or e-commerce applications. Visually sorted grid layouts attempt to arrange images so that their proximity on the grid corres
Externí odkaz:
http://arxiv.org/abs/2205.04255
The native macOS application PicArrange integrates state-of-the-art image sorting and similarity search to enable users to get a better overview of their images. Many file and image management features have been added to make it a tool that addresses
Externí odkaz:
http://arxiv.org/abs/2111.13363
Even though it has extensively been shown that retrieval specific training of deep neural networks is beneficial for nearest neighbor image search quality, most of these models are trained and tested in the domain of landmarks images. However, some a
Externí odkaz:
http://arxiv.org/abs/2111.13122
Nowadays stock photo agencies often have millions of images. Non-stop viewing of 20 million images at a speed of 10 images per second would take more than three weeks. This demonstrates the impossibility to inspect all images and the difficulty to ge
Externí odkaz:
http://arxiv.org/abs/1910.06005
One of the key challenges of deep learning based image retrieval remains in aggregating convolutional activations into one highly representative feature vector. Ideally, this descriptor should encode semantic, spatial and low level information. Even
Externí odkaz:
http://arxiv.org/abs/1909.09420
In recent years, deep metric learning has achieved promising results in learning high dimensional semantic feature embeddings where the spatial relationships of the feature vectors match the visual similarities of the images. Similarity search for im
Externí odkaz:
http://arxiv.org/abs/1909.09427
Akademický článek
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Autor:
Taeger, Dirk, McCunney, Robert, Bailer, Ursula, Barthel, Kai, Küpper, Ulrich, Brüning, Thomas, Morfeld, Peter, Merget, Rolf
Publikováno v:
Journal of Occupational and Environmental Medicine, 2016 Apr 01. 58(4), 376-384.
Externí odkaz:
https://www.jstor.org/stable/48500964
