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Deep Learning for Image Retrieval: What Works and What ...
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由 H Wang 著作2015被引用 56 次 — Abstract: To build an industrial content-based image retrieval system (CBIRs), it is highly recommended that feature extraction, feature processing and ...
(PDF) Deep Learning for Image Retrieval: What Works and ...
ResearchGate
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2016年7月28日 — PDF | On Nov 1, 2015, Huafeng Wang and others published Deep Learning for Image Retrieval: What Works and What Doesn't | Find, read and cite ...
Deep Learning for Image Retrieval
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由 H Wang 著作2015被引用 56 次 — We here provide a quick summary to highlight what works and what doesn't for using deep learning in image retrieval. Generalization Capacity of Feature ...
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Deep Learning for Image Retrieval: What Works and What ...
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Deep Learning for Image Retrieval: What Works and What Doesn't · Huafeng Wang, Yehe Cai, +3 authors. Hao Han · Published in IEEE International Conference… 14 ...
Effective and Scalable Manifold Ranking-Based Image ...
Department of Computer Science and Engineering - HKUST
https://cse.hkust.edu.hk › ~raywong › paper › tk...
Department of Computer Science and Engineering - HKUST
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由 D LIN 著作2023被引用 2 次 — Due to the rapid growth of deep learning approaches, more better feature vectors of images could be discovered for improving image retrieval. However, most (if ...
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An Effective Deep Learning Model for Content-Based ...
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In this regard, deep learning concept helps in choosing appropriate features for retrieval. In this work, Content-Based Image Retrieval system is proposed using ...
Deep Learning Based Multimodal Image Retrieval Combining ...
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由 MI Sarker 著作被引用 2 次 — The system starts a query triggered by input image and text while taking the help of the Transformer model, which puts attention on both modalities and combines ...
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Content-based image retrieval example using Deep Neural ...
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Content-based Image Retrieval using deep neural networks is overall much more accurate and faster both in creating the database and search times but it consumes ...
Inspired by Computer Vision & Deep Learning Techniques
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2020年7月16日 — Most of the current Content. Based Image Retrieval systems works with basic level image features like color, texture, shape. We can think of.
Optimization of deep convolutional neural network for large ...
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由 C Bai 著作2018被引用 132 次 — Feature extraction and similarity measurement are two key steps in image retrieval. AlexNet is a classical deep convolutional neural network ...
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