Handwritten isolated Bangla compound character recognition: A new benchmark using a novel deep learning approach
TLDR
A novel deep learning technique for the recognition of handwritten Bangla isolated compound character is presented and a new benchmark of recognition accuracy on the CMATERdb 3.3.1.3 dataset is reported.About:
This article is published in Pattern Recognition Letters.The article was published on 2017-04-15 and is currently open access. It has received 113 citations till now. The article focuses on the topics: Deep learning & Artificial neural network.read more
Citations
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Journal Article
Document Analysis and Recognition
TL;DR: This paper addresses current topics about document image understanding from a technical point of view as a survey and proposes methods/approaches for recognition of various kinds of documents.
Journal ArticleDOI
A multi-scale deep quad tree based feature extraction method for the recognition of isolated handwritten characters of popular indic scripts
TL;DR: In the present work, a non-explicit feature based approach, more specifically, a multi-column multi-scale convolutional neural network (MMCNN) based architecture has been proposed for this purpose and a deep quad-tree based staggered prediction model has be proposed for faster character recognition.
Proceedings ArticleDOI
Bangla Handwritten Character Recognition using Convolutional Neural Network with Data Augmentation
Rumman Rashid Chowdhury,Mohammad Shahadat Hossain,Raihan Ul Islam,Karl Andersson,Sazzad Hossain +4 more
TL;DR: A process of Handwritten Character Recognition to recognize and convert images of individual Bangla handwritten characters into electronically editable format is proposed, which will create opportunities for further research and can also have various practical applications.
Journal ArticleDOI
The short-term interval prediction of wind power using the deep learning model with gradient descend optimization
TL;DR: A deep interval prediction method is designed in the framework of LUBE and an efficient gradient descend (GD) training approach is proposed to train the LubE model and results show that the proposed approach performs best in terms of effectiveness and efficiency.
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Reshaping inputs for convolutional neural network: Some common and uncommon methods
TL;DR: Empirical evidence is intended to provide empirical evidence to guide the reader to choose a proper technique of reshaping inputs for their convolutional neural networks.
References
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Proceedings Article
ImageNet Classification with Deep Convolutional Neural Networks
TL;DR: The state-of-the-art performance of CNNs was achieved by Deep Convolutional Neural Networks (DCNNs) as discussed by the authors, which consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.
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Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan,Andrew Zisserman +1 more
TL;DR: This work investigates the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting using an architecture with very small convolution filters, which shows that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 weight layers.
Proceedings Article
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan,Andrew Zisserman +1 more
TL;DR: In this paper, the authors investigated the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting and showed that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 layers.
Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Journal ArticleDOI
Gradient-based learning applied to document recognition
Yann LeCun,Léon Bottou,Léon Bottou,Yoshua Bengio,Yoshua Bengio,Yoshua Bengio,Patrick Haffner +6 more
TL;DR: In this article, a graph transformer network (GTN) is proposed for handwritten character recognition, which can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters.