Filters








70,779 Hits in 5.0 sec

Neural Codes for Image Retrieval [article]

Artem Babenko, Anton Slesarev, Alexandr Chigorin, Victor Lempitsky
2014 arXiv   pre-print
Overall, our quantitative experiments demonstrate the promise of neural codes as visual descriptors for image retrieval.  ...  In this paper, we investigate the use of such descriptors (neural codes) within the image retrieval application.  ...  Independently and in parallel with our work, the use of neural codes for image retrieval (among other applications) has been investigated in [20] .  ... 
arXiv:1404.1777v2 fatcat:rzhl4fk5pbfljjlslxvkrbfn4q

Neural Codes for Image Retrieval [chapter]

Artem Babenko, Anton Slesarev, Alexandr Chigorin, Victor Lempitsky
2014 Lecture Notes in Computer Science  
Overall, our quantitative experiments demonstrate the promise of neural codes as visual descriptors for image retrieval.  ...  In this paper, we investigate the use of such descriptors (neural codes) within the image retrieval application.  ...  Independently and in parallel with our work, the use of neural codes for image retrieval (among other applications) has been investigated in [20] .  ... 
doi:10.1007/978-3-319-10590-1_38 fatcat:s3ad4dk34jgdbawkkorr7wseba

Generating Binary Tags for Fast Medical Image Retrieval Based on Convolutional Nets and Radon Transform [article]

Xinran Liu, Hamid R. Tizhoosh, Jonathan Kofman
2016 arXiv   pre-print
We combine neural codes for global classification with Radon barcodes for the final retrieval. We also examine image search based on regions of interest (ROI) matching after image retrieval.  ...  The present work introduces a new image retrieval method for medical applications that employs a convolutional neural network (CNN) with recently introduced Radon barcodes.  ...  Image Retrieval Result The convolutional neural network was trained for 50 epochs, which took 5 hours on a NVIDIA Tesla C2050 GPU.  ... 
arXiv:1604.04676v1 fatcat:lljgqct2szeoraifrzvfmjxfra

ANALYSIS OF IMAGE STORAGE AND RETRIEVAL IN GRADED MEMORY

B Sudarshan .
2015 International Journal of Research in Engineering and Technology  
An approach to storing and retrieving static images using multilayer Hopfield neural network is analyzed. Here, the Hopfield network is used as a memory, which stores images in predefined resolution.  ...  During the image retrieval, down sampled version of the stored image is provided as the query mage, The memory initially gives out a coarse image.  ...  The stored images can be retrieved by providing the corresponding down sampled image as the input to the neural network.  ... 
doi:10.15623/ijret.2015.0404136 fatcat:ckqb4dx7crfjrdlqobvnr5ko6q

Deep hash for latent image retrieval

Fanfeng Zeng, Shengda Hu, Ke Xiao
2019 Multimedia tools and applications  
The most advanced method is using a deep neural network to get hash code of images to achieve fast image retrieval at present.  ...  The experimental results show that the proposed method is better than most existing hash-based image retrieval methods.  ...  As convolutional neural networks have powerful feature extraction capabilities, some methods called deep hash that use convolutional neural networks to generate hash code for image retrieval have emerged  ... 
doi:10.1007/s11042-019-07980-9 fatcat:atl4mhq6zvfxlag6gr2oznummi

SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs

Jamil Ahmad, Muhammad Sajjad, Irfan Mehmood, Sung Wook Baik, Gayle E. Woloschak
2017 PLoS ONE  
The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval.  ...  OPEN ACCESS Citation: Ahmad J, Sajjad M, Mehmood I, Baik SW (2017) SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs.  ...  Acknowledgments The authors thank courtesy of TM Deserno, Dep. of Medical Informatics, RWTH Aachen, Germany, for providing IRMA dataset.  ... 
doi:10.1371/journal.pone.0181707 pmid:28771497 pmcid:PMC5542646 fatcat:vseqnumxhncafpz2gmpneb6opi

A Decade Survey of Content Based Image Retrieval using Deep Learning [article]

Shiv Ram Dubey
2020 arXiv   pre-print
Generally, the similarity between the representative features of the query image and dataset images is used to rank the images for retrieval.  ...  This paper presents a comprehensive survey of deep learning based developments in the past decade for content based image retrieval.  ...  Convolutional Neural Networks for Image Retrieval The convolutional neural networks (CNN) based feature learning has been utilized extensively for image retrieval.  ... 
arXiv:2012.00641v1 fatcat:2zcho2szpzcc3cs6uou3jpcley

Efficient image retrieval using multi neural hash codes and bloom filters [article]

Sourin Chakrabarti
2020 arXiv   pre-print
This paper aims to deliver an efficient and modified approach for image retrieval using multiple neural hash codes and limiting the number of queries using bloom filters by identifying false positives  ...  Traditional approaches involving neural networks for image retrieval tasks tend to use higher layers for feature extraction.  ...  We propose a unique approach of using neural codes from multiple layers simultaneously for image retrieval tasks and pre-query filtering tasks.  ... 
arXiv:2011.03234v2 fatcat:w32yhjl4dvdnbamy6toflqyvxe

Efficient image retrieval using multi neural hash codes and bloom filters

Sourin Chakrabarti
2020 Asian journal of convergence in technology  
This paper aims to deliver an efficient and modified approach for image retrieval using multiple neural hash codes and limiting the number of queries using bloom filters by identifying false positives  ...  Traditional approaches involving neural networks for image retrieval tasks tend to use higher layers for feature extraction.  ...  We propose a unique approach of using neural codes from multiple layers simultaneously for image retrieval tasks and pre-query filtering tasks.  ... 
doi:10.33130/ajct.2020v06i03.004 fatcat:7s473euc7feuvpwzln32a57mw4

Deep Learning Hash for Wireless Multimedia Image Content Security

Yu Zheng, Jiezhong Zhu, Wei Fang, Lian-Hua Chi
2018 Security and Communication Networks  
IDLH performs image retrieval by the deep neural networks (DNN) as well as image classification with the binary hash codes.  ...  An improved image deep learning hash (IDLH) method to learn compact binary codes for image search is proposed in this paper.  ...  In [27] , a deep neural network was developed to learn multilevel nonlinear transformations, mapping the original image to a compact binary hash code to support large-scale image retrieval for learning  ... 
doi:10.1155/2018/8172725 fatcat:lh5jfindm5d6fayemyamv4cyou

Minimize the Percentage of Noise in Biomedical Images Using Neural Networks

Abdul Khader Jilani Saudagar
2014 The Scientific World Journal  
The novelty of this technique lies in the implementation of spectral coding for biomedical images using neural networks in order to accomplish the above objectives.  ...  The overall goal of the research is to improve the quality of biomedical image for telemedicine with minimum percentages of noise in the retrieved image and to take less computation time.  ...  Acknowledgments The author is very much thankful to Al Imam Mohammad Ibn Saud Islamic University for providing an environment to carry out this research successfully.  ... 
doi:10.1155/2014/757146 pmid:25136685 pmcid:PMC4127272 fatcat:byrxldpmvnbevkphdtb73z4x6u

Mask Assisted Object Coding with Deep Learning for Object Retrieval in Surveillance Videos

Kezhen Teng, Jinqiao Wang, Min Xu, Hanqing Lu
2014 Proceedings of the ACM International Conference on Multimedia - MM '14  
Experimental results show our approach significantly outperforms state-of-the-art solutions for object retrieval in large-scale video dataset.  ...  Specifically, we take advantage of the mask information to assist object representation, and develop an encoding method by utilizing highly nonlinear mapping with a deep neural network.  ...  The object image and mask image are used to learn multimodel deep neural network that map similar objects to similar binary codes.  ... 
doi:10.1145/2647868.2654981 dblp:conf/mm/TengWXL14 fatcat:y4bthrdlrnd3voqj3mgkuv2d6a

Large-scale Image Retrieval using Neural Net Descriptors

David Novak, Michal Batko, Pavel Zezula
2015 Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '15  
Keywords metric indexing; deep convolutional neural network; contentbased image retrieval; k-NN search ONLINE IMAGE RETRIEVAL SYSTEM One of current big challenges in computer science is development of  ...  The applicability of such a system would be, for instance, on stock photography sites, in e-shops searching in product photos, or in collections from a constrained Web image search.  ...  distance-based index PPP-Codes [5] which organizes 320 GB of neural network descriptors extracted from a collection of 20 million images; given a query image, the memory part of the index is able to  ... 
doi:10.1145/2766462.2767868 dblp:conf/sigir/NovakBZ15 fatcat:ehofgbfl5ra6jagjbe52ytyojm

Annotation of enhanced radiographs for medical image retrieval with deep convolutional neural networks

Obioma Pelka, Felix Nensa, Christoph M Friedrich
2018 PLoS ONE  
The Image Retrieval in Medical Applications (IRMA) Code, a mono-hierarchical multi-axial code, served as a basis for this work.  ...  retrieval (CBIR) and computer-aided diagnosis (CAD).  ...  Deserno from the Department of Medical Informatics, RWTH Aachen Germany, for providing us with ImageCLEF 2009 Medical Annotation training and test sets.  ... 
doi:10.1371/journal.pone.0206229 pmid:30419028 pmcid:PMC6231616 fatcat:x6gmeiumovdqpnrowcm2vtdey4

Video retrieval based on deep convolutional neural network [article]

Yj Dong, JG Li
2017 arXiv   pre-print
As an extension of image hashing techniques, traditional video hashing methods mainly depend on hand-crafted features and transform the real-valued features into binary hash codes.  ...  As videos provide far more diverse and complex visual information than images, extracting features from videos is much more challenging than that from images.  ...  more challenging than image retrieval.  ... 
arXiv:1712.00133v1 fatcat:zf2lnzivcffmbkg3cwztqvypjy
« Previous Showing results 1 — 15 out of 70,779 results