Vector of Locally and Adaptively Aggregated Descriptors for Image Feature Representation
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Vector of Locally and Adaptively Aggregated Descriptors for Image Feature Representation
Authors
Keywords
VLAD, Deep learning, Weighting scheme, Gating scheme, Feature representation
Journal
PATTERN RECOGNITION
Volume 116, Issue -, Pages 107952
Publisher
Elsevier BV
Online
2021-03-19
DOI
10.1016/j.patcog.2021.107952
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Graph Convolutional Network with Structure Pooling and Joint-wise Channel Attention for Action Recognition
- (2020) Yuxin Chen et al. PATTERN RECOGNITION
- Multiple Attentional Pyramid Networks for Chinese Herbal Recognition
- (2020) Yingxue Xu et al. PATTERN RECOGNITION
- MuLTReNets: Multilingual text recognition networks for simultaneous script identification and handwriting recognition
- (2020) Zhuo Chen et al. PATTERN RECOGNITION
- Image classification base on PCA of multi-view deep representation
- (2019) Yaoqi Sun et al. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
- Improving text classification with weighted word embeddings via a multi-channel TextCNN model
- (2019) Bao Guo et al. NEUROCOMPUTING
- Saliency Inside: Learning Attentive CNNs for Content-Based Image Retrieval
- (2019) Shikui Wei et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking
- (2019) Daniel Carlos Guimaraes Pedronette et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Spatial Pyramid-Enhanced NetVLAD With Weighted Triplet Loss for Place Recognition
- (2019) Jun Yu et al. IEEE Transactions on Neural Networks and Learning Systems
- Locality-constrained affine subspace coding for image classification and retrieval
- (2019) Bingbing Zhang et al. PATTERN RECOGNITION
- Hierarchical Deep Click Feature Prediction for Fine-Grained Image Recognition
- (2019) Jun Yu et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Dynamic Match Kernel with Deep Convolutional Features for Image Retrieval
- (2018) Jufeng Yang et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- NetVLAD: CNN Architecture for Weakly Supervised Place Recognition
- (2018) Relja Arandjelovic et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Improved spatial pyramid matching for scene recognition
- (2018) Lin Xie et al. PATTERN RECOGNITION
- Visual interpretability for deep learning: a survey
- (2018) Quan-shi Zhang et al. Frontiers of Information Technology & Electronic Engineering
- Geometry and Topology Preserving Hashing for SIFT Feature
- (2018) Chen Kang et al. IEEE TRANSACTIONS ON MULTIMEDIA
- Fisher vector for scene character recognition: A comprehensive evaluation
- (2017) Cunzhao Shi et al. PATTERN RECOGNITION
- Handcrafted vs. non-handcrafted features for computer vision classification
- (2017) Loris Nanni et al. PATTERN RECOGNITION
- Three-stream CNNs for action recognition
- (2017) Liangliang Wang et al. PATTERN RECOGNITION LETTERS
- Training-Based Gradient LBP Feature Models for Multiresolution Texture Classification
- (2017) Luping Ji et al. IEEE Transactions on Cybernetics
- A hierarchal BoW for image retrieval by enhancing feature salience
- (2016) Fan Jiang et al. NEUROCOMPUTING
- Visual Place Recognition with Repetitive Structures
- (2015) Akihiko Torii et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Learning to Rank Using User Clicks and Visual Features for Image Retrieval
- (2015) Jun Yu et al. IEEE Transactions on Cybernetics
- Aggregating Local Image Descriptors into Compact Codes
- (2011) H. Jegou et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationPublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More