A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Filters
End-to-End Text Classification via Image-based Embedding using Character-level Networks
[article]
2018
arXiv
pre-print
The proposed CE-CLCNN is an end-to-end learning model and has an image-based character encoder, i.e. the CE-CLCNN handles each character in the target document as an image. ...
open document classification tasks. ...
[15] explicitly learned to preserve character shape features by CAE, but our CE-CLCNN does not explicitly learn character representation that preserves the shape Fig. 3 . ...
arXiv:1810.03595v2
fatcat:43yhkxnnanh5nfh2xrzbuzje44
SF-CNN: Deep Text Classification and Retrieval for Text Documents
2023
Intelligent Automation and Soft Computing
for retrieving correct text documents. ...
Traditional deep learning methods such as Convolutional Neural Network and Recurrent Neural Network never use semantic representation for bag-of-words. ...
The proposed SF-CNN method enhances the semantic features for classifying and retrieving research documents better than traditional methods. ...
doi:10.32604/iasc.2023.027429
fatcat:r2czwj5p6jdntkr3lgkp23erma
Discretization based learning approach to information retrieval
2005
Proceedings of the 14th ACM international conference on Information and knowledge management - CIKM '05
We approached the problem as learning how to order documents by estimated relevance with respect to a user query. ...
For this, we have designed a representation scheme, which is based on the discrete representation of the local (lw) and global (gw) weighting functions, thus is capable of reproducing and enhancing the ...
Figure 1 . 1 Learning local weighting for various
Figure 3 . 3 Learned optimal shape of local weighting.
Figure 4 . 4 Learned optimal shape of global weighting G(t). ...
doi:10.1145/1099554.1099647
dblp:conf/cikm/RoussinovFN05a
fatcat:ziy7zvhobjesxl2ze3uz5txgku
F-ratio Based Weighted Feature Extraction for Similar Shape Character Recognition
2009
2009 10th International Conference on Document Analysis and Recognition
This weighting scheme enhances the feature elements that belongs to the distinguishable portions of the similar shaped characters and reduces the feature elements of the common portion of the characters ...
Fratio modifies the feature vector of two similar shape characters by weighting the feature elements. ...
F-ratio is calculated from feature vectors belong to the similar shaped character classes and enhanced the feature vector for better recognition. ...
doi:10.1109/icdar.2009.197
dblp:conf/icdar/WakabayashiPKM09
fatcat:tsbvmggm7jcn5ghjnqbtnecu7q
Supplementary document for Unsupervised Hyperspectral Stimulated Raman Microscopy Image Enhancement: Denoising and Segmentation via One-Shot Deep Learning - 5472694.pdf
2021
figshare.com
Unsupervised Hyperspectral Image Enhancement, Segmentation and De-Noising in Stimulated Raman Microscopy: supplemental document 1. ...
S4 The spatial distribution of the PSNR for FOV1 for the data presented inFig. 5for (a) Input-GT, (b) SHRED-GT, and (c) UHRED-GT. ...
doi:10.6084/m9.figshare.16705603.v1
fatcat:safluluck5a2fh4mh3esmt4o44
CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor
[article]
2019
arXiv
pre-print
To avoid designing expert rules for each specific type of document, some published works attempt to tackle the problem by learning a model to explore the semantic context in text sequences based on the ...
Extracting key information from documents, such as receipts or invoices, and preserving the interested texts to structured data is crucial in the document-intensive streamline processes of office automation ...
Furthermore, to enhance the capability of CUTIE to better handle documents with different layouts, we augment the grid data to shapes with different rows and columns by random sampling a Gaussian distribution ...
arXiv:1903.12363v4
fatcat:ra73l3owrzftngnuohw5ftnkhy
The Role and Utilization of CNN in Automatic Logo Based Document Image Retrieval Methods
2018
International Journal of Engineering & Technology
Automatic logo based document image retrieval process is an essential and mostly used method in the feature extraction applications. ...
The main objective of this paper is to effectively utilize the CNN in the process of automatic logo based document image retrieval methods. ...
R.Vinoth Kanna sir for his continuous supportive encouragement in my research work done so far including this paper. ...
doi:10.14419/ijet.v7i3.1.16786
fatcat:i7rwnytolffarejeiyfzankf3u
Enhanced visual statistical learning in adults with autism
2015
Neuropsychology
Conclusions: These results extend previous observations of visuospatial enhancement in ASD into the domain of learning, and suggest that enhanced visual statistical learning may have arisen from a sustained ...
bias to attend to local details in complex arrays of visual features. ...
For example, a circular-shaped clock and a wheel share a feature ("roundness"), but it is a defining feature only for the wheel. ...
doi:10.1037/neu0000137
pmid:25151115
pmcid:PMC4340818
fatcat:cxblkrea35btbdk5if73bkdyle
How Does Learning Impact Development in Infancy? The Case of Perceptual Organization
2010
Infancy
The proposed framework is an attempt to account for this process in the domain of perception. ...
However, other processes are not readily evident in young infants, and their development involves perceptual learning. ...
For instance, being exposed to correlations between two features (say, shape and color: shape A being red always and shape B being blue always) in the context of other varying features (say, size: shapes ...
doi:10.1111/j.1532-7078.2010.00048.x
pmid:21572570
pmcid:PMC3092381
fatcat:jfbssft5rvctrhznsrka5su5xa
HANDWRITTEN DEVANAGARI VOWEL RECOGNITION USING ARTIFICIAL NEURAL NETWORK
2017
International Journal of Advanced Research in Computer Science
Human being is doing this task while learning characters in the childhood. But the same task for machine is much complex. ...
This research work proposes new approaches for extracting features in context of Handwritten Devanagari Vowels recognition. For classification technique Artificial Network is used. ...
HOG features describe the shape of the image by the distribution of intensity gradients or edge directions. A HOG feature vector represents local shape of an object [12, 13] . ...
doi:10.26483/ijarcs.v8i7.4560
fatcat:2bbqhg72erd3tfhid4sgsurzka
Document Image Retrieval Based on Keyword Spotting Using Relevance Feedback
2013
International Journal of Engineering
Keyword Spotting is a well-known method in document image retrieval which is based on query word image. ...
In this paper, a document image retrieval system based on keyword spotting and relevance feedback is presented. ...
[15] proposed a new feedback approach with progressive learning capability combined with a novel method for feature subspace extraction. ...
doi:10.5829/idosi.ije.2014.27.01a.02
fatcat:nqqnogjecngexol6wdwb3h3rg4
A brief review of document image retrieval methods: Recent advances
2016
2016 International Joint Conference on Neural Networks (IJCNN)
This paper provides an overview of the methods which have been applied for document image retrieval over recent years. ...
Many techniques have been developed to provide an efficient and effective way for retrieving and organizing these document images in the literature. ...
The indexing/learning methods are applied to train a classifier or knowledge-based method for some given documents. ...
doi:10.1109/ijcnn.2016.7727648
dblp:conf/ijcnn/AlaeiABP16
fatcat:5tzfmk55r5hmpa3tnhcj3chuji
An enhanced binarization framework for degraded historical document images
2021
EURASIP Journal on Image and Video Processing
It uses a disk-shaped structuring element, whose radius is computed by the minimum entropy-based stroke width transform (SWT). ...
AbstractBinarization plays an important role in document analysis and recognition (DAR) systems. ...
First, we can improve the contrast between text and background by using machine learning or deep learning techniques to effectively achieve degraded document image enhancement in the preprocessing stage ...
doi:10.1186/s13640-021-00556-4
fatcat:aawmkhjf3ngs3bb3zbyyi4xz5q
A Framework for Content Sequencing from Junior to Senior Mathematics Curriculum
2022
Eurasia Journal of Mathematics, Science and Technology Education
a tool for sequencing the mathematics content. ...
Planning templates and samples are available to schools; however, it is imperative for teachers to understand the processes that underpin planning. ...
Shapes and intercepts, asymptotes shapes and behavior and features, center and radii can all be brought under features of graphs. 2. ...
doi:10.29333/ejmste/11930
fatcat:fymdxhhnyzew7otuwl7ydudsu4
Image analysis for digital media applications
2001
IEEE Computer Graphics and Applications
Acknowledgment Our work on cartoon image analysis, handwriting recognition, and document image compression is supported by several grants from the Australian Research Council. ...
detection 1
Shape from shading: finding 3D shapes from 2D images
Relaxation labeling: object matching 13
1 Example of image enhancement:
(a) the original color image and
(b) the enhanced image. ...
For example, we can achieve a high recognition rate for well-isolated characters by integrating several classifiers. 9 In research, useful ideas can be learned from a different field. ...
doi:10.1109/38.895126
fatcat:pfhnkx3zyrhtpmpwchb7dhg4ym
« Previous
Showing results 1 — 15 out of 244,134 results