N.I.Te provides innovative software technologies for automatic document processing, especially handwritten documents, both off-line from static images, and on-line from handwriting coordinates acquired by several devices. NITe’s technology is able to read handwritten words also without a lexicon and not provided to the system during the learning step, overcoming the limits of the others solutions in the market. Another important advantage of the technology is the capability of learning from a reduced data set of training samples, which makes convenient also for small companies and institutions with a reduced documental heritage using an automatic system for data capture. The technology is independent from any writer, alphabet and reference language and more in details it is able to:
Read
Extraction and automatic reading of textual information, such as characters, digits and cursive handwriting from both structured and free-form handwritten documents
Search
Automatically indexing and spotting words of interest in digital archives containing handwritten documents, from the 17th century to modern times.
Analyze
Quantitative evaluation of both static and dynamic features of handwriting.
Products
Masquerade is a software for the analysis and the evaluation of morphological and dynamic features of handwriting. The software is tailored for handwriting experts, both from forensic and HR sectors, is able to automatically measure handwriting features and reduce the time needed to produce a report.
HandBiblio is a software for indexing and searching by keywords in handwritten documents contained in huge digital archives (modern or historical). The software is particularly recommended for libraries, professional firms, private companies and public institutions that need to manage their digital heritage. HandBiblio is also quickly customizable on any dataset of words, and able to learn from a reduced dataset of samples, obtaining a reduction of the time and cost for the customers.
InkReadable is a software for extracting and automatically reading information in digital documents, mainly handwritten documents. The software is able to automatically process structured and not structured documents by reading numeric and alphabetic fields and also handwritten words, not provided to the system during the learning step, by dynamically changing and quickly updating the lexicon, if required
About US
Natural Intelligent Technologies (N.I.Te) was born in 28 May 2012 as a spin-off company of the University of Salerno. Our mission is to commercialize the technologies created and developed in the Natural Computational Laboratory (NCLab). N.I.Te provides innovative technologies and advanced software solutions for automatic processing of digital documents, especially handwritten. The proposed solutions are based on an innovative and patented technology developed in twenty years of research, for automatically reading cursive handwritten documents. Our target customers are SME companies and public institutions which need automatic solutions to manage their digital archives.
Our Team
ADOLFO SANTORO
CEO of N.I.Te
He holds a M. Eng. degree in Electronic Engineering from University of Salerno, working on a project on handwriting recognition, and a PostGraduate Master in Air Traffic Control at Selex Sistemi Integrati, a FinMeccanica company. He has been a Research Fellow at the Natural Computation Lab working on a project on handwritten postal address recognition. He is in charge of the strategic and operational management of the company
ANTONIO PARZIALE
CTO of N.I.Te
He received a M.Eng. in Electronic Engineering and a Ph.D. in Information Engineering both from University of Salerno working on computational model of the spinal neural circuitry in motor learning and execution. He has been a PostDoc at the Natural Computation Lab leading the research activity on forensic analysis of forged handwritten documents, and is currently Assistant professor at the University of Salerno. He is in charge of the technical development of NITe technology and products.
ROSA SENATORE
CIO of N.I.Te
She received a M.Eng. in Electronic Engineering and a Ph.D. in Information Engineering both from University of Salerno working on neuro-computational model of the basal ganglia in in motor learning and execution. She spent a year as visiting Ph.D. candidate at Brown University, USA, and has been a PostDoc at the Natural Computation Lab, leading the research activity on handwriting analysis for early diagnosis of neurodegenerative diseases. She is leading the R&D activities of the company.
Angelo Marcelli
Full Professor of Artificial Intelligence at Engineering Faculty of University of Salerno Salerno and Director of Natural Computation Laboratory. He has more than twenty years long experience in research project management and he is in charge of management of Intellectual property.
Claudio De Stefano
Full Professor of Artificial Intelligence at Engineering Faculty of University of Cassino, he works on research topics related to Pattern Recognition and Artificial Intelligence.