[PDF] Top 20 A Learning State-Space Model for Image Retrieval
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A Learning State-Space Model for Image Retrieval
... the state. We first have to design a scheme for representing the state, which intuitively handles the semantic gap between vi- sual features and user ...semantic space for image ... See full document
10
Content-Based Image Retrieval using Deep Learning
... consists of the same parameters i.e. weights and bias that form a feature map. We can see in fig.4.2 that same feature map contains 3 hidden units. The weights of same color are shared that are constrained to be ... See full document
44
Findings on ranking evaluation functions for feature weighting in image retrieval
... information retrieval and recommendation ...the image retrieval ...(RF) model, called WLSP-C ± , aimed at improving image retrieval results through the use of learning ... See full document
10
Dual Space Re ranking Model for Document Retrieval
... language model scores, through a weighted version of the PageRank algorithm (Kurland and Lee, 2005) and a HITS-style cluster-based approach (Kurland and Lee, ...document retrieval rankings from an initial ... See full document
9
Query Mining for Automatic Annotation and Annotation Based Image Retrieval Using Hidden Markov Model
... training image defined, estimation of the HMM parameters proceeds in a standard manner as prescribed in ...(annotated image+caption pairs), we proceed to decoding the ...one state of model ... See full document
7
Dual Space Re ranking Model for Document Retrieval
... language model scores, through a weighted version of the PageRank algorithm (Kurland and Lee, 2005) and a HITS-style cluster-based approach (Kurland and Lee, ...document retrieval rankings from an initial ... See full document
9
Information Retrieval System By Using Vector Space Model
... regional state of Ethiopia and also academic language for primary school of the ...Information Retrieval (IR) is one of the major branches of Information Science discipline ...and retrieval can be ... See full document
7
Scalable Database Indexing and Fast Image Retrieval Based on Deep Learning and Hierarchically Nested Structure Applied to Remote Sensing and Plant Biology
... the retrieval process and reduces memory usage substantially ...query image to each and every single feature vector in the ...entire image dataset might be feasible for small datasets, this is still ... See full document
22
Deep Learning based Enhanced Triplet Nework Model for Landmark Classification in Image Retrieval
... In this preferred method, for the purpose of recognition of landmark we can use triplet network. In this Work, prefer a Convolutional neural network (CNN) on the basis of Triplet networks algorithm with the help of ... See full document
8
Privacy Issues in Content based Image Retrieval (CBIR) for Mobile Users, and a Proposed Solution
... such image retrieval problem, that searches for digital images in large databases by analyzing the contents of the image rather than the metadata or descriptions associated with the ...deep ... See full document
6
Exploring Multi-Modal and Structured Representation Learning for Visual Image and Video Understanding
... deep model which fuses complementary information derived from multiple CNN side ...new state of the art results for the monocular depth estimation task on three publicly available datasets, ... See full document
93
Recovery of Myocardial Kinematic Function without the Time History of External Loads
... the state-space-based motion recovery algorithms with the external loads constructed from boundaries [21, 24] and model-based filtering framework with external loads simulated from an ... See full document
9
Active Learning Method for Interactive Image Retrieval
... large space of image and video databases has become more ...the image and high-level user semantics. How to achieve accurate retrieval results are still a challenging and an unsolved research ... See full document
6
IMAGE RETRIEVAL: A STATE OF THE ART APPROACH FOR CBIR
... the retrieval performance in content- based image ...on learning an ‘optimal’ correspondence between the high-level semantic concepts and the low-level internal features in each query ...multimedia ... See full document
7
Attribute-enhanced metric learning for face retrieval
... metric learning model to learn the reformed metrics ...top-16 retrieval results in similarity retrieval since the number of displays in interac- tive retrieval is also ...similarity ... See full document
9
Face Image Retrieval Techniques : A Survey
... between image pairs; yet, both methods produce compact visual descriptions, and work on real-world ...current state-of-the-art for the LFW data set, reducing the error rates compared to the current best by ... See full document
8
Secure Privacy-Preserving Content-Based Retrieval in Cloud Image Repositories
... of image contents by directly computing the image features from an ...The image features are directly constructed from the typical Block Truncation Coding or half toning based compressed data stream ... See full document
6
Efficient Image Retrieval Using Cloud Repository
... i.e. image and ...the image arrays and audio entities, and they defined the metric of the distance between the means for the measurement of similarity; therefore an optimization strategy based on relevant ... See full document
8
A Novel Content Based Image Retrieval Implemented By NSA Of AIS
... Based Image Retrieval system was developed long back, a technique using visual content according to the interests of the users', to search images from large scale image ...of retrieval is ... See full document
5
Image Mediated Learning for Zero Shot Cross Lingual Document Retrieval
... We also verified the effect of the performance of image features in our framework (see Figure 5 and Table 3). CNN has improved dramatically over the last few years, and many new powerful pre-trained networks are ... See full document
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