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Automatic image annotation with continuous PLSA
2010
2010 IEEE International Conference on Acoustics, Speech and Signal Processing
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Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. ...
Furthermore, in order to deal with the data of different modalities in terms of their characteristics, we present a semantic annotation model which employs continuous PLSA and standard PLSA to model visual ...
In order to model image data precisely, it is required to deal with continuous quantity using PLSA. ...
doi:10.1109/icassp.2010.5494943
dblp:conf/icassp/LiSLS10
fatcat:7yvkivlqafcivlymmhm3xi5efe
A Novel Model for Semantic Learning and Retrieval of Images
[chapter]
2012
IFIP Advances in Information and Communication Technology
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Then, we apply this model in automatic image annotation. ...
In order to deal with the data of different modalities according to their characteristics, we present a semantic annotation model which employs continuous PLSA and traditional PLSA to model visual features ...
As a result, automatic image annotation has emerged as a crucial problem for semantic image retrieval. ...
doi:10.1007/978-3-642-32891-6_42
fatcat:tabgiv7zsff2nphd3gf6z2kggi
Combining Generative/Discriminative Learning for Automatic Image Annotation and Retrieval
2012
International Journal of Intelligence Science
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In order to bridge the semantic gap exists in image retrieval, this paper propose an approach combining generative and discriminative learning to accomplish the task of automatic image annotation and retrieval ...
We firstly present continuous probabilistic latent semantic analysis (PLSA) to model continuous quantity. ...
We evaluate the performance of image annotation by comparing the captions automatically generated with the original manual annotations. ...
doi:10.4236/ijis.2012.23008
fatcat:y7mhhjarejhlpleycxh6fsdwuu
Modeling continuous visual features for semantic image annotation and retrieval
2011
Pattern Recognition Letters
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Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. ...
Furthermore, in order to deal with the data of different modalities in terms of their characteristics, we present a semantic annotation model which employs continuous PLSA and standard PLSA to model visual ...
We evaluate the performance of image annotation by comparing the captions automatically generated with the original manual annotations. ...
doi:10.1016/j.patrec.2010.11.015
fatcat:eewmqy6qsnbh3ohlqluc3o5c7m
Automatic Image Annotation and Retrieval Using Hybrid Approach
[chapter]
2012
IFIP Advances in Information and Communication Technology
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We firstly propose continuous probabilistic latent semantic analysis (PLSA) to model continuous quantity. ...
Furthermore, we present a hybrid framework which employs continuous PLSA to model visual features of images in generative learning stage and uses ensembles of classifier chains to classify the multi-label ...
We evaluate the performance of image annotation by comparing the captions automatically generated with the original manual annotations. ...
doi:10.1007/978-3-642-32891-6_43
fatcat:3vxgwdaqrndejclzglsv27guea
Multilabel Image Annotation Based on Double-Layer PLSA Model
2014
The Scientific World Journal
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Due to the semantic gap between visual features and semantic concepts, automatic image annotation has become a difficult issue in computer vision recently. ...
Experimental results demonstrate that our automatic image annotation model based on double-layer PLSA can achieve promising performance for labeling and outperform previous methods on standard Corel dataset ...
Image Annotation Model Based on Double-Layer PLSA Image automatic annotation algorithm based on double-layer PLSA fully utilizes the visual and semantic information of images to construct the annotation ...
doi:10.1155/2014/494387
pmid:24999490
pmcid:PMC4066723
fatcat:3b2cryf3n5ewbhe42bip3ejqhu
Extended Probabilistic Latent Semantic Analysis for Automatic Image Annotation
2017
Journal of Information Hiding and Multimedia Signal Processing
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efficiency in the task of automatic image annotation. ...
So in this paper, we propose a novel extended probabilistic latent semantic analysis (PLSA) to improve the performance of automatic image annotation. ...
In the recent past, many PLSA models for automatic image annotation are limited by the scope of the representation. ...
dblp:journals/jihmsp/Tian17a
fatcat:3sgydjovbvbgfdulhkj725o3eu
Research on PLSA Model based Semantic Image Analysis: A Systematic Review
2018
Journal of Information Hiding and Multimedia Signal Processing
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So the current paper, to begin with, elaborates the basic principles of the PLSA model, followed by summarizes PLSA with applications to image annotation, image retrieval, image classification and several ...
However, compared with various PLSA models and their corresponding applications in semantic image analysis, there is almost no review research and analysis about PLSA related studies. ...
automatic image annotation. ...
dblp:journals/jihmsp/Tian18b
fatcat:jbhuva4bq5akdldkdkba3fseda
Semantic Image Annotation based on Robust Probabilistic Latent Semantic Analysis
2017
Journal of Information Hiding and Multimedia Signal Processing
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In this paper, we present a robust probabilistic latent semantic analysis (PLSA) for the task of automatic image annotation. ...
Automatic image annotation is a promising solution to enable the semantic image retrieval via keywords. ...
Especially in the research [11] , a PLSA model with asymmetric modalities was embedded into the Markov random fields for automatic image annotation. ...
dblp:journals/jihmsp/Tian17
fatcat:ol4spdpwxjgx3k6obdydblrf2q
A Weighted Topic Model Learned from Local Semantic Space for Automatic Image Annotation
2020
IEEE Access
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Automatic image annotation plays a significant role in image understanding, retrieval, classification, and indexing. ...
INDEX TERMS Automatic image annotation, image retrieval, probabilistic latent semantic analysis, topic model. III. PROPOSED APPROACH A. THE AIA FRAMEWORK ...
Figure 1 shows our proposed LL-PLSA framework for automatic image annotation. ...
doi:10.1109/access.2020.2989200
fatcat:rn4xkw2lojg7td6k723cqbuwdi
Refining Image Annotation by Integrating PLSA with Random Walk Model
[chapter]
2013
Lecture Notes in Computer Science
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In this paper, we present a new method for refining image annotation by integrating probabilistic latent semantic analysis (PLSA) with random walk (RW) model. ...
First, we construct a PLSA model with asymmetric modalities to estimate the posterior probabilities of each annotating keywords for an image, and then a label similarity graph is constructed by a weighted ...
To address these limitations, automatic image annotation (AIA) has become a focus and received extensive investigation, whose purpose is to automatically assign some keywords to an image that can well ...
doi:10.1007/978-3-642-35725-1_2
fatcat:nnoy73wpczhazbb7ehbmrgsyey
Semantic spaces revisited
2008
Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR '08
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This paper discusses three different formulations for building semantic spaces which allow the automatic-annotation and semantic retrieval of images. ...
The paper also discusses how these termbased models compare to the latest state-of-the-art continuous feature models for auto-annotation and retrieval. ...
various other automatic annotation techniques compare to the linearalgebraic technique and PLSA-Words Models Co-Occurrence Translation CMRM PLSA-Words LASS CRM MBRM SML Words with Recall > 0 19
49
66 ...
doi:10.1145/1386352.1386399
dblp:conf/civr/HareSLN08
fatcat:swllyiiszrgsxmhpeb7ofmcvke
A Survey on Automatic Image Annotation and Retrieval
2015
International Journal of Computer Applications
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Automatic image annotation technique can be based on various things either it can observe the images various ways either in texture bases, colour intensity basis or faces included or involved into the ...
The Image Annotation process are required to use automated where the strong tagging is required to keep annotate image for making it efficient to provide better results while querying those image annotated ...
Gaussian-Multinomial PLSA (GM-PLSA): GM-PLSA is a combination of two PLSA models: a standard PLSA to model textual words and a continuous PLSA to model visual features. ...
doi:10.5120/20863-3575
fatcat:rllnqwclezcnvm5j5qfbqcjhaq
Modeling Semantic Aspects for Cross-Media Image Indexing
2007
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this paper, we present three alternatives to learn a Probabilistic Latent Semantic Analysis (PLSA) model for annotated images and evaluate their respective performance for automatic image indexing. ...
The first learning procedure of a PLSA model for annotated images is a standard Expectation-Maximization (EM) algorithm, which implicitly assumes that the visual and the textual modalities can be treated ...
The paper is organized as follows: Section 2 presents an overview of the research in automatic image annotation and contrasts it with our work. ...
doi:10.1109/tpami.2007.1097
pmid:17699924
fatcat:tccktjz4sje5rlmfsaimegm2p4
Continuous visual vocabulary modelsfor pLSA-based scene recognition
2008
Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR '08
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The performance of these continuous vocabulary models are compared in an automatic scene recognition task. ...
Our experiments clearly show that the continuous approaches outperform the standard pLSA model. ...
] , scene recognition [11] , automatic image segmentation and image annotation [2] . ...
doi:10.1145/1386352.1386395
dblp:conf/civr/HorsterLS08
fatcat:m6lz4trytbf6xowgm4fy2btzca
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