March 22, 2017- <\/p>\n
Neurotechnology has released SentiVeillance 6.0 software development kit (SDK), which provides improved facial recognition using up to 10 surveillance, security and public safety cameras on a single computer, making it suitable for a wide range of surveillance applications. <\/p>\n
According to a company statement, the new version uses deep neural-network-based facial detection and recognition algorithms to improve accuracy, and it utilizes a Graphing Processing Unit (GPU) for enhanced speed. In addition, users can more quickly and easily adjust the tradeoff between speed and accuracy as needed for different applications. <\/p>\n
We developed SentiVeillance 6.0 as a self-adapting system based on deep neural networks that were trained on a larger quantity of data, said Ignas Namajunas, surveillance technologies research lead for Neurotechnology. This ensures better generalization for a variety of conditions. Additionally, by making use of the GPU processing capabilities, we were able to improve the processing speed significantly. <\/p>\n
As with previous versions, the new SentiVeillance provides: real-time moving object detection; tracking and classification for pedestrians, vehicles and other predefined object classes based on size and speed of movement, and; area control that triggers events when people or objects enter, leave or stay in restricted areas. <\/p>\n
comments <\/p>\n
<\/p>\n
Follow this link:<\/p>\n
Neurotechnology releases new SentiVeillance SDK - Biometric Update<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" March 22, 2017- Neurotechnology has released SentiVeillance 6.0 software development kit (SDK), which provides improved facial recognition using up to 10 surveillance, security and public safety cameras on a single computer, making it suitable for a wide range of surveillance applications. According to a company statement, the new version uses deep neural-network-based facial detection and recognition algorithms to improve accuracy, and it utilizes a Graphing Processing Unit (GPU) for enhanced speed. In addition, users can more quickly and easily adjust the tradeoff between speed and accuracy as needed for different applications. Continue reading