News Article | July 26, 2017
JERICHO, N.Y.--(BUSINESS WIRE)--Intellicheck, Inc. (NYSE MKT:IDN), an industry leader in delivering real-time threat identification and identification authentication that provides the antivirus to the epidemic of counterfeit IDs, today announced that Michael McDonald, Business Development Manager for Law Enforcement Solutions, has been elected to the IJIS Board of Directors. McDonald was elected by vote of the membership of the organization. Founded in 2001 as the Integrated Justice Information Systems Institute, the IJIS Institute is a nonprofit organization whose members are industry leading information technology companies that unite the private and public sectors to improve critical information sharing. The Institute plays a major role in the development of national standards from policy to technology enabling information sharing in public safety, justice and homeland security communities by working collaboratively with local, state, tribal and federal agencies. The Institute focuses on national priorities including mission-critical initiatives. McDonald is a former Delaware State Trooper who rose to the rank of Major and has 21 years of law enforcement experience followed by an 18-year career as the civilian Director of the Delaware State Police Information Technology Section. As the Director, McDonald represented the state of Delaware as the CJIS Systems Officer to the FBI and was also the state’s Nlets representative. He served on the Nlets (International Justice and Public Safety Network) Board of Directors and in executive leadership positions on the FBI’s Advisory Policy Board before joining Intellicheck. McDonald has extensive experience in federal, tribal, state, and local law enforcement, and criminal justice agency information sharing environments. He is nationally recognized as a leader in identifying issues, resolving impediments, and implementing solutions to support criminal justice agency information sharing environments at all levels. Intellicheck is an industry leader in providing cutting-edge technology solutions that are unique in their ability to provide accurate, real-time identification authentication and situational awareness that is fully regulatory compliant and easily integrated and customized into existing infrastructures including mobile devices. Its identity solutions support customers in the national defense, law enforcement, retail, hospitality and financial markets. Intellicheck is the industry leader in technology solutions that are the antivirus to the epidemic of counterfeit IDs providing real-time threat identification and identification authentication. Our technology solutions make it possible for our clients to enhance the safety and awareness of their facilities and people, improve customer service, and increase operational efficiencies. Founded in 1994, Intellicheck has grown to serve dozens of Fortune 500 companies including retail and financial industry clients, police departments, national defense clients at agencies, major seaports, and military bases, and diverse state and federal government agencies. The Company holds 25 patents including many patents pertaining to identification technology. For more information on Intellicheck, visit http://www.intellicheck.com/ and follow Intellicheck on Twitter @IntellicheckIDN, on Instagram @IntellicheckIDN, on LinkedIn https://www.linkedin.com/company/intellicheck-inc, on Facebook https://www.facebook.com/intellicheckidn/, on YouTube https://www.youtube.com/user/ICMOBIL, and read Intellicheck’s latest blog post at http://intellicheckidn.com/. Statements in this news release about Intellicheck’s future expectations, including: the advantages of our products, future demand for Intellicheck’s existing and future products, whether revenue and other financial metrics will improve in future periods, whether Intellicheck will be able to execute its turn-around plan or whether successful execution of the plan will result in increased revenues, whether sales of our products will continue at historic levels or increase, whether brand value and market awareness will grow, whether the Company can leverage existing partnerships or enter into new ones, and all other statements in this release, other than historical facts, are “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995 (PSLRA). These statements, which express management’s current views concerning future events, trends, contingencies or results, appear at various places in this website and use words like “anticipate,” “assume,” “believe,” “continue,” “estimate,” “expect,” “forecast,” “future,” “intend,” “plan,” “potential,” “predict,” “project,” “strategy,” “target” and similar terms, and future or conditional tense verbs like “could,” “may,” “might,” “should,” “will” and “would” are forward-looking statements within the meaning of the PSLRA. This statement is included for the express purpose of availing Intellicheck, Inc. of the protections of the safe harbor provisions of the PSLRA. It is important to note that actual results and ultimate corporate actions could differ materially from those in such forward-looking statements based on such factors as market acceptance of Intellicheck’s products and the presently anticipated growth in the commercial adoption of the Company’s products and services, changing levels of demand for Intellicheck’s current and future products, Intellicheck’s ability to reduce or maintain expenses while increasing sales, customer results achieved using our products in both the short and long term, success of future research and development activities, Intellicheck’s ability to successfully manufacture, market and sell its products, Intellicheck’s ability to manufacture its products in sufficient quantities to meet demand within required delivery time periods while meeting its quality control standards, any delays or difficulties in the Company’s supply chain, the success of the Company’s sales and marketing efforts coupled with the typically long sales and implementation cycle for its products, Intellicheck’s ability to enforce its intellectual property rights, changes in laws and regulations applicable to the Company’s products, the Company’s continued ability to access government-provided data, the risks inherent in doing business with the government including audits and contract cancellations, liability resulting from any security breaches or product failure, and other risks detailed from time to time in Intellicheck’s reports filed with the SEC. We do not assume any obligation to update the forward-looking information.
Solewicz Y.A.,Technology Section |
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH | Year: 2011
This paper presents a novel self-contained two-wire speaker recognition framework. The classical approach to two-wire speaker recognition usually requires a preliminary explicit speaker segmentation stage in order to extract audio files for the two hypothesized speakers. We propose an implicit speaker segmentation method implemented at the supervector level of speaker recognition systems. By periodically extracting successive supervectors from the two-wire audio it is possible to further associate them to each of the hypothesized speakers before scoring both streams. We show that the proposed technique leads to recognition performance comparable to standard approaches while requiring substantially less resources. Copyright © 2011 ISCA.
Yifrach A.,Ben - Gurion University of the Negev |
Novoselsky E.,Ben - Gurion University of the Negev |
Solewicz Y.A.,Technology Section |
Yitzhaky Y.,Ben - Gurion University of the Negev
Pattern Analysis and Applications | Year: 2016
The illumination variation is one of the well-known problems in face recognition under uncontrolled environments. Several techniques have been presented in the literature to cope up with this problem. Lately, a technique known as Nuisance Attribute Projection (NAP), originally developed for the speaker recognition field was introduced to image processing in order to compensate for luminance artifacts. This paper extends and improves the earlier work by exploring efficient methodologies for using NAP for face recognition under varied illumination conditions. In particular, we propose a modified NAP formulation and show that NAP training can be simplified for face recognition. Additionally, we suggested a compact framework merging between NAP compensation and eigenface recognition. A series of experiments using the extended YaleB database, and a cross-validation using the PIE CMU and the Oulo databases are performed to validate our proposals. © 2014, Springer-Verlag London.