Given video streams, we aim to correctly detect unsegmented signs related to continuous
sign language recognition (CSLR). Despite the increase in proposed deep learning …

Integrated convolutional neural network (CNN) and deep bidirectional long short-term
memory (DBLSTM) based character models have achieved excellent recognition accuracies …

Attention-based encoder-decoder approaches have shown promising results in scene text
recognition. In the literature, models with different encoders, decoders and attention …

The accuracy of a typical state-of-the-art optical character recognition (OCR) system benefits
greatly from using a language model (LM). However, a conventional LM has a limited …

We present two weighted finite-state transducer (WFST) based decoders for handwriting
recognition. One decoder is a cloud-based solution that is both compact and efficient. The …

Character models based on convolutional neural network (CNN) and deep bidirectional
long short-term memory (DBLSTM) have achieved high recognition accuracy on various …

The long short-term memory (LSTM) network with gating mechanism has been widely used
in sequence modeling tasks including handwriting and speech recognition. As an LSTM …

Automatic classification of dynamic hand gesture is challenging due to the large diversity in
a different class of gesture, Low resolution, and it is performed by finger. Due to a number of …

The authors describe the implementation of SISMAPEO, a database system designed to
manage brain electrical activity mapping (BEAM) information which enables practitioners to …

Hand gestures are the most natural, friendly, useful and intuitive non-verbal communication
medium while using a computer or machine, and related research efforts have recently …