Advances in online handwritten recognition in the last decades
The easy availability and rapid use of online devices like Take note, PDA, smartphones, etc.
at an affordable price increase the demand for online handwriting recognition. In this …
at an affordable price increase the demand for online handwriting recognition. In this …
Convolutional-neural-network-based handwritten character recognition: an approach with massive multisource data
Neural networks have made big strides in image classification. Convolutional neural
networks (CNN) work successfully to run neural networks on direct images. Handwritten …
networks (CNN) work successfully to run neural networks on direct images. Handwritten …
OCR-nets: variants of pre-trained CNN for Urdu handwritten character recognition via transfer learning
Deep Convolutional neural networks (CNN) have been among the utmost competitive
neural network architectures and have set the state-of-the-art in various fields of computer …
neural network architectures and have set the state-of-the-art in various fields of computer …
A two-stage deep feature selection method for online handwritten bangla and devanagari basic character recognition
In this paper, we have proposed a two-stage deep feature selection (FS) approach for the
recognition of online handwritten Bangla and Devanagari basic characters. At the beginning …
recognition of online handwritten Bangla and Devanagari basic characters. At the beginning …
[PDF][PDF] Deep learning based handwriting recognition with adversarial feature deformation and regularization
YB Hamdan, A Sathesh - Journal of innovative image processing, 2021 - researchgate.net
Due to the complex and irregular shapes of handwritten text, it is challenging to spot and
recognize the handwritten words. In low-resource scripts, retrieval of words is a difficult and …
recognize the handwritten words. In low-resource scripts, retrieval of words is a difficult and …
Hybrid DBLSTM-SVM based beta-elliptic-CNN models for online Arabic characters recognition
The deep learning-based approaches have proven highly successful in handwriting
recognition which represents a challenging task that satisfies its increasingly broad …
recognition which represents a challenging task that satisfies its increasingly broad …
Classification of handwritten Malayalam characters using a HOG-DCNN model with multiview augmentation and inference fusion
B Jose, P KP - Multimedia Tools and Applications, 2024 - Springer
Abstract Malayalam Handwriting Character Recognition (MHCR) is a challenging job
because of its large number of similar or confusing characters. This is especially true in the …
because of its large number of similar or confusing characters. This is especially true in the …
Intelligent handwritten character recognition for Malayalam scripts using deep learning approach
Abstract Machine Learning, especially Deep Learning has been incorporated into Pattern
Recognition and Image Processing for the Handwritten Character Recognition (HCR) …
Recognition and Image Processing for the Handwritten Character Recognition (HCR) …
A deep learning approach to recognize handwritten telugu character using convolution neural networks
Automated character recognition is one of the most vital components which enable a data
processor to distinguish letters and digits possibly using contextual data. Various attempts at …
processor to distinguish letters and digits possibly using contextual data. Various attempts at …
Reducing noise using neighbourhood pixel analysis and interpretable custom kernel in CNN model for CP handwritten digit recognition
Abstract Individuals with Cerebral Palsy (CP) are impacted lifetime barriers in their everyday
activities, especially in writing phrase, which results from innate neural motor in co …
activities, especially in writing phrase, which results from innate neural motor in co …