Add to ORKGIn this paper we present our latest experiments on the utilization of the recently developed Spatio-Temporal Artificial Neuron (STAN). This neuron has the capability to process asynchronous (continuous) spatio-temporal data sequences and compare them with the help of Hermitian distance. The problem addressed is that of online cursive (non-isolated) handwritten character recognition. We develop a system based on three modules: pre-processing, feature detection and character classification. The results obtained are encouraging and we also suggest further avenues of improvement in the system
Off-line handwriting recognition has wider applications than on-line recognition, yet it seems to be...
flannGnick.cs.usu.edu This paper introduces a new recognition-based segmentation ap-proach to recogn...
We describe a connectionist model for recognizing handprinted characters. Instead of treating the in...
Comparisons are made between a number of stroke-based and character-based recognizers of connected c...
This paper describes a new hybrid architecture for an artificial neural network classifier that enab...
w ai bel CO) cs. cm u. ed u In this paper we present NPen ++, a connectionist system for writer inde...
Character Recognitions The literature on Character verification is quite extensive and shows two mai...
This paper presents a system for large vocabulary recognition of on-line handwritten cursive words. ...
Abstract- This paper describes a neural network-based technique for cursive character recognition ap...
This paper presents a writer independent system for large vocabulary recognition of on-line handwrit...
Abstract- This paper describes a neural network-based technique for cursive character recognition ap...
This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recogniti...
Optical character recognition (OCR) software has advanced greatly in recent years. Machine-printed t...
Abstract- In this paper, we present a new neural network based method for handwritten character reco...
This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recogniti...
Off-line handwriting recognition has wider applications than on-line recognition, yet it seems to be...
flannGnick.cs.usu.edu This paper introduces a new recognition-based segmentation ap-proach to recogn...
We describe a connectionist model for recognizing handprinted characters. Instead of treating the in...
Comparisons are made between a number of stroke-based and character-based recognizers of connected c...
This paper describes a new hybrid architecture for an artificial neural network classifier that enab...
w ai bel CO) cs. cm u. ed u In this paper we present NPen ++, a connectionist system for writer inde...
Character Recognitions The literature on Character verification is quite extensive and shows two mai...
This paper presents a system for large vocabulary recognition of on-line handwritten cursive words. ...
Abstract- This paper describes a neural network-based technique for cursive character recognition ap...
This paper presents a writer independent system for large vocabulary recognition of on-line handwrit...
Abstract- This paper describes a neural network-based technique for cursive character recognition ap...
This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recogniti...
Optical character recognition (OCR) software has advanced greatly in recent years. Machine-printed t...
Abstract- In this paper, we present a new neural network based method for handwritten character reco...
This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recogniti...
Off-line handwriting recognition has wider applications than on-line recognition, yet it seems to be...
flannGnick.cs.usu.edu This paper introduces a new recognition-based segmentation ap-proach to recogn...
We describe a connectionist model for recognizing handprinted characters. Instead of treating the in...