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2019 IEEE Transactions on Image Processing  
Kautz 723 Semi-Supervised Metric Learning-Based Anchor Graph Hashing for Large-Scale Image Retrieval ...................... .............................................................................  ...  Zhang 965 Learning Effective RGB-D Representations for Scene Recognition ..... X. Song, S. Jiang, L. Herranz, and C.  ... 
doi:10.1109/tip.2018.2878279 fatcat:zxdnanrxtffl7hk2nvjjuwgp7m

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TIP 2021 1570-1582 Fast Local Spatial Verification for Feature-Agnostic Large-Scale Image Retrieval. Brogan, J., +, TIP 2021 6892-6905 Fast Manifold Ranking With Local Bipartite Graph.  ...  ., +, TIP 2021 7926-7937 Learning Efficient Hash Codes for Fast Graph-Based Data Similarity Retrieval.  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
Zhao, Y., +, TIP 2020 1591-1605 Adaptive Graph Representation Learning for Video Person Re-Identifica- tion.  ...  Henschel, R., +, TIP 2020 8476-8489 Adaptive Graph Representation Learning for Video Person Re-Identifica- tion.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Efficient Visual Recognition

Li Liu, Matti Pietikäinen, Jie Qin, Wanli Ouyang, Luc Van Gool
2020 International Journal of Computer Vision  
binary codes for personal- ized image retrieval Personalized image retrieval A general framework for deep supervised discrete hashing Image retrieval Product quantization network for fast visual  ...  The underlying data structures are discovered by adaptively learning a discriminative data graph.  ... 
doi:10.1007/s11263-020-01351-w fatcat:mbcq6shmerbo5njayscgb3t4rq

Anchor Graph Structure Fusion Hashing for Cross-Modal Similarity Search [article]

Lu Wang, Jie Yang, Masoumeh Zareapoor, Zhonglong Zheng
2022 arXiv   pre-print
Based on the anchor graph structure fusion matrix, AGSFH attempts to directly learn an intrinsic anchor graph, where the structure of the intrinsic anchor graph is adaptively tuned so that the number of  ...  AGSFH constructs the anchor graph structure fusion matrix from different anchor graphs of multiple modalities with the Hadamard product, which can fully exploit the geometric property of underlying data  ...  As opposed to pre-computing affinity graphs, in Eq.( 7 ), the affinity of the adaptive anchor graph Ŝ, i.e., ŝij , is learned by modeling fused anchor graph  from multiple modalities.  ... 
arXiv:2202.04327v1 fatcat:oxdytmhxyzavnetqbobl4dueka

2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30

2020 IEEE transactions on circuits and systems for video technology (Print)  
., +, TCSVT Sept. 2020 2797- 2800 Content-based retrieval Node-Sensitive Graph Fusion via Topo-Correlation for Image Retrieval.  ...  Azghani, M., +, TCSVT June 2020 1550-1558 Node-Sensitive Graph Fusion via Topo-Correlation for Image Retrieval.  ...  A Memory-Efficient Hardware Architecture for Connected Component Labeling in Embedded System.  ... 
doi:10.1109/tcsvt.2020.3043861 fatcat:s6z4wzp45vfflphgfcxh6x7npu

Character index

2011 2011 IEEE International Conference on Multimedia and Expo  
DICTIONARY LEARNING SPARSE REPRESENTATION BASED BLIND IMAGE DEBLURRING LEARNING THE SPARSE REPRESENTATION FOR CLASSIFICATION ALBUM-BASED OBJECT-CENTRIC EVENT RECOGNITION 09/08/2011 file://F:\HTML\Authors.html  ...  STUDENTS' PERCEIVED SATISFACTION, BEHAVIORAL INTENTION, AND EFFECTIVENESS OF ENGLISH LEARNING USING AUGMENTED REALITY Thomas Huang EFFICIENT SPARSE REPRESENTATION BASED IMAGE SUPER RESOLUTION VIA DUAL  ... 
doi:10.1109/icme.2011.6011827 fatcat:wjy7yvkmvbbf3hj4wbyjapx5gu

BoundaryNet: An Attentive Deep Network with Fast Marching Distance Maps for Semi-automatic Layout Annotation [article]

Abhishek Trivedi, Ravi Kiran Sarvadevabhatla
2021 arXiv   pre-print
The network optimization is guided via Fast Marching distance maps to obtain a good quality initial boundary estimate and an associated feature representation.  ...  Fully automatic boundary estimation approaches tend to be data intensive, cannot handle variable-sized images and produce sub-optimal results for aforementioned images.  ...  Despite the challenges posed by such images, a number of deep-learning based approaches have been proposed for fully automatic layout parsing [35, 30, 3, 26] .  ... 
arXiv:2108.09433v1 fatcat:ins2mli7ozd6rhp3basekbddjm

Large Scale Video Representation Learning via Relational Graph Clustering

Hyodong Lee, Joonseok Lee, Joe Yue-Hei Ng, Paul Natsev
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Representation learning is widely applied for various tasks on multimedia data, e.g., retrieval and search.  ...  One approach for learning useful representation is by utilizing the relationships or similarities between examples.  ...  Conclusion In this work, we propose two novel methods that learn video representations from pairwise similarity structure via graph clustering: Graph Clustering Metric Learning (GCML), using ranking loss  ... 
doi:10.1109/cvpr42600.2020.00684 dblp:conf/cvpr/LeeLNN20 fatcat:ecbnuoukerdlnb3h6qwbl3wo5q

Dual-level Semantic Transfer Deep Hashing for Efficient Social Image Retrieval [article]

Lei Zhu, Hui Cui, Zhiyong Cheng, Jingjing Li, Zheng Zhang
2020 arXiv   pre-print
Deep hashing is an efficient indexing technique to support large-scale social image retrieval, due to its deep representation capability, fast retrieval speed and low storage cost.  ...  Moreover, the hash codes are obtained simultaneously with the deep representation learning by the discrete hash optimization strategy.  ...  in the social image dataset, the fast social image retrieval can be achieved.  ... 
arXiv:2006.05586v1 fatcat:whuawurklfbinl7fs6mg5kqw4q

Unsupervised Deep Cross-modality Spectral Hashing [article]

Tuan Hoang and Thanh-Toan Do and Tam V. Nguyen and Ngai-Man Cheung
2020 arXiv   pre-print
In the second step, to learn mapping functions from informative data inputs (images and word embeddings) to binary codes obtained from the first step, we leverage the powerful CNN for images and propose  ...  This paper presents a novel framework, namely Deep Cross-modality Spectral Hashing (DCSH), to tackle the unsupervised learning problem of binary hash codes for efficient cross-modal retrieval.  ...  Graph * / 1 Learn anchor sets for modalities (Sec.  ... 
arXiv:2008.00223v3 fatcat:i2xbdck5gncinhai362j2xnmpu

2021 Index IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 43

2022 IEEE Transactions on Pattern Analysis and Machine Intelligence  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TPAMI Sept. 2021 3183-3195 FNA++: Fast Network Adaptation via Parameter Remapping and Architecture Search.  ...  ., +, TPAMI July 2021 2373-2387 FNA++: Fast Network Adaptation via Parameter Remapping and Architec-ture Search.  ... 
doi:10.1109/tpami.2021.3126216 fatcat:h6bdbf2tdngefjgj76cudpoyia

CLARA: Clinical Report Auto-completion [article]

Siddharth Biswal, Cao Xiao, Lucas M. Glass, M. Brandon Westover, and Jimeng Sun
2020 arXiv   pre-print
The retrieved sentences are sequentially modified by combining with the input feature representations to create the final report.  ...  We propose CLinic Al Report Auto-completion (CLARA), an interactive method that generates reports in a sentence by sentence fashion based on doctors' anchor words and partially completed sentences.  ...  the index with new documents easily so new reports can be integrated; 3) The query response is much faster than a typical prototype learning model thanks to the fast retrieval system.  ... 
arXiv:2002.11701v2 fatcat:w76c2mqxizag7m3lip3wgaqmtu

Robust and Scalable Graph-Based Semisupervised Learning

Wei Liu, Jun Wang, Shih-Fu Chang
2012 Proceedings of the IEEE  
Graph-based semisupervised learning methods and new techniques for handling contaminated noisy labels, and gigantic data sizes for web applications, are reviewed in this paper.  ...  retrieval.  ...  Z ij 's are the local supports of anchors for each data point x i .  ... 
doi:10.1109/jproc.2012.2197809 fatcat:fk66s5zl75d35pn3rjwmhver7a

ARtwin: Map pivot format specification

Nam Duong Duong, Jérôme Royan, Michal Polic, Nischita Sudharsan
2020 Zenodo  
This project has received funding from the European Union's Horizon 2020 Framework Programme for research and Innovation under Grant Agreement no 856994.  ...  Early feature aggregation techniques for image retrieval rely on BoW representations [44] , [93] .  ...  Image retrieval approaches Image retrieval approaches include two main elements. The first one is the image retrieval model that allows calculating global feature representation for each keyframe.  ... 
doi:10.5281/zenodo.4381408 fatcat:pn2ioshymfcrrkbuhxg72kr7zy
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