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Document image decoding using Iterated Complete Path search with subsampled heuristic scoring
Proceedings of Sixth International Conference on Document Analysis and Recognition
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It has been shown that the computation time of Document Image Decoding can be significantly reduced by employing heuristics in the search for the best decoding of a text line. ...
We present the optimal (lowest upperbound) heuristic for any degree of subsampling of multilevel template and/or interpolation, for use in text line decoding with ICP. ...
In this introduction, we give a quick review of the fundamental parameters and equations for a DID line decoder, and then describe the Iterated Complete Path (ICP) algorithm. ...
doi:10.1109/icdar.2001.953811
dblp:conf/icdar/BloombergPM01
fatcat:dsi5zvfizngetdivwz5tl54zbu
Document image decoding using iterated complete path search
2000
Document Recognition and Retrieval VIII
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The computation time of Document Image Decoding can be significantly reduced by employing heuristics in the search for the best decoding of a text line. ...
In the Iterated Complete Path method, template matches are performed only along the best path found by dynamic programming on each iteration. ...
ACKNOWLEDGEMENTS This work is a direct outgrowth of the pioneering work by Gary Kopec and Phil Chou, and we wish to dedicate it to Gary, who is no longer with us to share in the fruits of his creativity ...
doi:10.1117/12.410843
dblp:conf/drr/MinkaBP01
fatcat:wvtupuranbefpnrasdw56sbqpm
Adding linguistic constraints to document image decoding: comparing the iterated complete path and stack algorithms
2000
Document Recognition and Retrieval VIII
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Beginning with an observed document image and a model of how the image has been degraded, Document Image Decoding recognizes printed text by attempting to find a most probable path through a hypothesized ...
The first, called the iterated complete path algorithm, involves iteratively rescoring complete paths using conditional language model probability distributions of increasing order, expanding state only ...
ACKNOWLEDGMENTS This work has benefitted from discussions with Henry Baird, Thorsten Brants, Tom Breuel, Francine Chen, Gary Kopec, Tom Minka, and Les Niles. ...
doi:10.1117/12.410844
dblp:conf/drr/PopatGRB01
fatcat:hq77qflv2vdytnckz3wsf4mjw4
Document Recognition without Strong Models
2011
2011 International Conference on Document Analysis and Recognition
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Can a high-performance document image recognition system be built without detailed knowledge of the application? ...
When we can't collect (and label) enough real training data, does it help to complement them with data synthesized using generative models? Is it ever completely safe to rely on synthetic data? ...
In response to this problem PARC researchers invented a procedure (iterated complete path optimization) to find an optimal path that is, on average, far faster [45] and compared it with an approximate ...
doi:10.1109/icdar.2011.91
dblp:conf/icdar/Baird11
fatcat:3mc4igzc3vd2llksd2hafvdtf4
Dynamic Boundary Time Warping for Sub-sequence Matching with Few Examples
[article]
2020
arXiv
pre-print
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Instead, we use query examples as is, utilizing all of them simultaneously. ...
We are the first to propose an algorithm for such a search that does not rely on computing the average sequence from query examples. ...
As shown by Wang and Jiang (1994) , multiple sequence alignment with the sum of all pairs score 2 is an NP-complete problem. ...
arXiv:2010.14464v1
fatcat:iq4liqjfxzbctkrvdocrswi4mm
High quality document image compression with "DjVu"
1998
Journal of Electronic Imaging (JEI)
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Then, several novel techniques are used to maximize the compression ratio: the bi-level foreground image is encoded with AT&T's proposal to the new JBIG2 fax standard, and a new wavelet-based compression ...
We present a new image compression technique called \DjVu " that is speci cally geared towards the compression of high-resolution, high-quality images of scanned documents in color. ...
Document Image Compression with DjVu As we stated earlier, the digital library experience cannot be complete without a way of transmitting and displaying document images in color. ...
doi:10.1117/1.482609
fatcat:zxve2ne2jjgzpbdmlftbtzgmc4
Minkowski's Inequality Based Sensitivity Analysis of Fuzzy Signatures
2016
Journal of Artificial Intelligence and Soft Computing Research
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Finally, we apply our results to a fuzzy signature used in civil enginnering. ...
In this paper we discuss the sensitivity of the weigthed general mean aggregation operator to the uncertainty of the input values, then we analyse the sensitivity of fuzzy signatures equipped with these ...
A t-test (with the significance level p=0.01) was used to compare these results with the F-score values obtained with the ensemble of classifiers in Experiment 4 (without any subsample exchange tech-nique ...
doi:10.1515/jaiscr-2016-0016
fatcat:tpmfrlnp3bhbznaqxztvl4hray
Graph-Based Keyword Spotting in Historical Documents Using Context-Aware Hausdorff Edit Distance
2018
2018 13th IAPR International Workshop on Document Analysis Systems (DAS)
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The decoded string can further be used as a query for database search, e.g. in document retrieval. ...
A language model can be used to improve decoding of the network output. Transcription, decoding and dictionary search are often seen as separate steps. ...
doi:10.1109/das.2018.31
dblp:conf/das/Stauffer0R18
fatcat:2r2cjpiitfcs5knjtqbfvcuwsi
On the applications of multimedia processing to communications
1998
Proceedings of the IEEE
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It provides access to distributed data bases and, via some excellent search engines, has excellent search capabilities. ...
With the emergence of the multimedia PC and its concomitant signal-processing capability, a simple solution was proposed, namely, the compression (and decompression) and coding (and decoding) of voice ...
image processing. ...
doi:10.1109/5.664272
fatcat:yhn4kb3mmbctbbfus7br26oox4
Generative chemistry: drug discovery with deep learning generative models
[article]
2020
arXiv
pre-print
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From the generation of original texts, images, and videos, to the scratching of novel molecular structures, the incredible creativity of deep learning generative models surprised us about the height machine ...
This review starts with a brief history of artificial intelligence in drug discovery to outline this emerging paradigm. ...
Notably, the complete de novo drug design cycle can be achieved with target prediction models for scoring. ...
arXiv:2008.09000v1
fatcat:ivznoc4bsbfoderwr2ted76fiq
NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commands
[article]
2021
arXiv
pre-print
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This is a report on the competition with details of the task, metrics, data, attempted solutions, and lessons learned. ...
Participants were tasked with building models that can transform descriptions of command line tasks in English to their Bash syntax. ...
Scores in the beam search were produced using an approximation 21 for confidence due to the high correlation observed between correct predictions and high beam scores. 3. ...
arXiv:2103.02523v2
fatcat:2wva6wca5jbhrfslqej5efj5wi
Advances in Electron Microscopy with Deep Learning
2020
Zenodo
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This doctoral thesis covers some of my advances in electron microscopy with deep learning. ...
, uniformly spaced and other fixed sparse scan paths; recurrent neural networks trained to piecewise adapt sparse scan paths to specimens by reinforcement learning; improving signal-to-noise; and conditional ...
In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license. ...
doi:10.5281/zenodo.4598227
fatcat:hm2ksetmsvf37adjjefmmbakvq
Advances in Electron Microscopy with Deep Learning
2020
Zenodo
Preserved Fulltext
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The file type is application/pdf.
This doctoral thesis covers some of my advances in electron microscopy with deep learning. ...
, uniformly spaced and other fixed sparse scan paths; recurrent neural networks trained to piecewise adapt sparse scan paths to specimens by reinforcement learning; improving signal-to-noise; and conditional ...
In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license. ...
doi:10.5281/zenodo.4591029
fatcat:zn2hvfyupvdwlnvsscdgswayci
Advances in Electron Microscopy with Deep Learning
2020
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
This doctoral thesis covers some of my advances in electron microscopy with deep learning. ...
, uniformly spaced and other fixed sparse scan paths; recurrent neural networks trained to piecewise adapt sparse scan paths to specimens by reinforcement learning; improving signal-to-noise; and conditional ...
In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license. ...
doi:10.5281/zenodo.4399748
fatcat:63ggmnviczg6vlnqugbnrexsgy
Advances in Electron Microscopy with Deep Learning
2020
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
This doctoral thesis covers some of my advances in electron microscopy with deep learning. ...
, uniformly spaced and other fixed sparse scan paths; recurrent neural networks trained to piecewise adapt sparse scan paths to specimens by reinforcement learning; improving signal-to-noise; and conditional ...
In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license. ...
doi:10.5281/zenodo.4413249
fatcat:35qbhenysfhvza2roihx52afuy
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