Handwritten text recognition using deep learning
A Nikitha, J Geetha… - … Conference on Recent …, 2020 - ieeexplore.ieee.org
There are many researchers working on handwritten text recognition (HTR) and also
contributing to HTR domain. Even though many research methods are existing for HTR …
contributing to HTR domain. Even though many research methods are existing for HTR …
Boosting modern and historical handwritten text recognition with deformable convolutions
Abstract Handwritten Text Recognition (HTR) in free-layout pages is a challenging image
understanding task that can provide a relevant boost to the digitization of handwritten …
understanding task that can provide a relevant boost to the digitization of handwritten …
Deep learning model for the inspection of coffee bean defects
SJ Chang, CY Huang - Applied Sciences, 2021 - mdpi.com
The detection of coffee bean defects is the most crucial step prior to bean roasting. Existing
defect detection methods used in the specialty coffee bean industry entail manual screening …
defect detection methods used in the specialty coffee bean industry entail manual screening …
The LAM dataset: a novel benchmark for line-level handwritten text recognition
S Cascianelli, V Pippi, M Maarand… - 2022 26th …, 2022 - ieeexplore.ieee.org
Handwritten Text Recognition (HTR) is an open problem at the intersection of Computer
Vision and Natural Language Processing. The main challenges, when dealing with …
Vision and Natural Language Processing. The main challenges, when dealing with …
When massive GPU parallelism ain't enough: A novel hardware architecture of 2D-LSTM neural network
V Rybalkin, J Ney, MK Tekleyohannes… - ACM Transactions on …, 2021 - dl.acm.org
Multidimensional Long Short-Term Memory (MD-LSTM) neural network is an extension of
one-dimensional LSTM for data with more than one dimension. MD-LSTM achieves state-of …
one-dimensional LSTM for data with more than one dimension. MD-LSTM achieves state-of …
Research on handwritten note recognition in digital music classroom based on deep learning
Y Wang - Journal of Internet Technology, 2021 - jit.ndhu.edu.tw
Music is an indispensable subject in quality education, which plays an important role in
improving students' overall quality. Traditional music teaching is mainly a one-way teaching …
improving students' overall quality. Traditional music teaching is mainly a one-way teaching …
A limited-size ensemble of homogeneous CNN/LSTMs for high-performance word classification
M Ameryan, L Schomaker - Neural Computing and Applications, 2021 - Springer
The strength of long short-term memory neural networks (LSTMs) that have been applied is
more located in handling sequences of variable length than in handling geometric variability …
more located in handling sequences of variable length than in handling geometric variability …
Efficient hardware architectures for 1D-and MD-LSTM networks
Abstract Recurrent Neural Networks, in particular One-dimensional and Multidimensional
Long Short-Term Memory (1D-LSTM and MD-LSTM) have achieved state-of-the-art …
Long Short-Term Memory (1D-LSTM and MD-LSTM) have achieved state-of-the-art …
Handwriting recognition using wasserstein metric in adversarial learning
Deep intelligence provides a great way to deal with understanding the complex handwriting
of the user. Handwriting is challenging due to its irregular shapes, which vary from one user …
of the user. Handwriting is challenging due to its irregular shapes, which vary from one user …
Development of a signature verification model based on a small number of samples
SJ Chang, TR Wu - Signal, Image and Video Processing, 2024 - Springer
In this study, an improved AlexNet and transfer learning architecture was used to construct a
signature recognition model based on a small number of samples to verify offline signatures …
signature recognition model based on a small number of samples to verify offline signatures …