Exploiting Category-Level Semantic Relationships for Fine-Grained Image Recognition

Xianjie Mo; Jia-Jie Zhu; Xiaoxuan Zhao; Min Liu; Tingting Wei; Wei Luo

doi:10.1007/978-3-030-31654-9_5

ScienceGate Book Chapters

BOOK-CHAPTER

Exploiting Category-Level Semantic Relationships for Fine-Grained Image Recognition

Xianjie Mo Jia-Jie Zhu Xiaoxuan Zhao Min Liu Tingting Wei Wei Luo

Year: 2019 Lecture notes in computer science Pages: 50-62 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-31654-9_5

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Discriminative model Artificial intelligence Benchmark (surveying) Metric (unit) Feature (linguistics) Machine learning Contrast (vision) Hierarchy Pattern recognition (psychology) Aggregate (composite) Regularization (linguistics) Tree (set theory)

Metrics

Cited By

0.26

FWCI (Field Weighted Citation Impact)

Refs

0.52

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Exploiting Category-Level Semantic Relationships for Fine-Grained Image Recognition

Metrics

Citation History

Topics

Related Documents

Category-specific Semantic Coherency Learning for Fine-grained Image Recognition

Cross-Category Cross-Semantic Regularization for Fine-Grained Image Recognition

Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding

A semantic-driven image scene fine-grained enhancement recognition

Fine-Grained Image Recognition