arXiv:2108.01542
공식 코드 · Papers with Code
iART: A Search Engine for Art-Historical Images to Support Research in the Humanities
원문 초록
In this paper, we introduce iART: an open Web platform for art-historical research that facilitates the process of comparative vision. The system integrates various machine learning techniques for keyword- and content-based image retrieval as well as category formation via clustering. An intuitive GUI supports users to define queries and explore results. By using a state-of-the-art cross-modal deep learning approach, it is possible to search for concepts that were not previously detected by trained classification models. Art-historical objects from large, openly licensed collections such as Amsterdam Rijksmuseum and Wikidata are made available to users.
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A Semantically-Aware Relevance Measure for Content-Based Medical Image Retrieval Evaluation
Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning
RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics Features
Orchestrator-Agent Trust: A Modular Agentic AI Visual Classification System with Trust-Aware Orchestration and RAG-Based Reasoning
Improving Personalized Search with Regularized Low-Rank Parameter Updates
MCoT-RE: Multi-Faceted Chain-of-Thought and Re-Ranking for Training-Free Zero-Shot Composed Image Retrieval
토론
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