Press Release
Neurotechnology Takes First Place in NIST ELFT for Accuracy and Ranks Among the Top Overall Performers
Neurotechnology's NIST ELFT submission showcased its latent fingerprint algorithm as the most accurate across most datasets and among best in extraction speed.
Vilnius, Lithuania – December 10, 2024 – Neurotechnology, a provider of deep learning-based solutions and high-precision biometric identification technologies, today announced that its latent fingerprint algorithm leads the National Institute of Standards and Technology (NIST) Evaluation of Latent Friction Ridge Technology (ELFT) in accuracy, while also ranking among the best in extraction speed. This achievement underscores the company's commitment to delivering industry-leading biometric technology for the law enforcement domain.
"We are thrilled to end this year with one more top-tier evaluation from NIST," said Evaldas Borcovas, Biometrics Research Team Lead for Neurotechnology. "ELFT represents the most advanced evaluation of fingerprint recognition for law enforcement applications. Our biometrics research team takes pride in this remarkable achievement, which highlights our unwavering commitment to advancing our technology and establishing new quality benchmarks in biometric recognition. This accomplishment reinforces our dedication to innovation and excellence, shaping the future of secure and reliable identification systems."
The NIST ELFT evaluation uses datasets from US government and law enforcement institutions, including the United States Department of Defense, FBI, and Michigan State Police, with the entire gallery comprising more than 1.6 million unique IDs. The evaluation tests how well a provider's algorithm can identify the right person using latent prints. It checks how often the algorithm misses the correct match or picks the wrong hit by mistake. It also measures the algorithm's ability to consistently identify the correct match on the first attempt or include it within the top 100 candidates, which later can be verified by a qualified professional.
Neurotechnology's latest submission achieved the best accuracy across most datasets, excelling in automatic identification and delivering correct matches for manual review if needed. The algorithm also ranks among the top performers in single-finger and latent feature extraction speed, offering an optimal balance of accuracy and performance.
About Neurotechnology
Neurotechnology is a developer of high-precision algorithms and software based on deep neural networks and other AI-related technologies. The company was launched in 1990 in Vilnius, Lithuania, with the key idea of leveraging neural network capabilities for various applications, such as biometric person identification, natural language processing (NLP), computer vision, and artificial intelligence. The company's solutions and products have been used in more than 140 countries worldwide and in many national-scale projects for national ID, passports, elections, law enforcement, and border control, including India's Aadhaar program, general elections in Ghana and Liberia, voter deduplication for the Democratic Republic of the Congo and other projects that collectively process the biometric data of nearly two billion people.
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Jennifer Allen Newton
Bluehouse Consulting Group, Inc.
+1-503-805-7540
jennifer (at) bluehousecg (dot) com
