Developing high-performance IoT solutions using OpenVino toolkit. Deep learning deployment kit, based on convolutional neural networks, combined with cross-platform flexibility and scalability of Intel® hardware architecture, significantly accelerates AI-workloads and assists business owners in real-time data processing, monitoring, and predictive analytics to drive business operations and enhance customer experience.
Recent Projects
Large semi-trucks manufacturer tasked Auriga to develop an optical recognition system for components to automate orders fulfillment, receipt or shipment of goods, inventory check, etc.
EU-based manufacturer of scanning digital microscopes tasked Auriga with development of an automated tool for biopsy plates mapping to improve time-response, reduce lab workload and errors, and contribute to better patient care.
A major industrial components manufacturer entrusted Auriga with modernization of the legacy anomaly detection system that sorts out defective parts on the production line.
A U.S. technological start-up specializing in security and video surveillance enterprise solutions tasked Auriga with developing autonomous module to identify vehicles on office parking areas to check available slots, detect traffic violation and generate smart events for security service.
An EU-based manufacturer of smart medical devices contracted Auriga’s data science team to R&D new medical image analysis algorithms to assist with automated detection of certain patterns in tissue images.
A global construction industry leader asked Auriga to conduct research and development for a new system to monitor the integrity of building structures (anchorage loosening detection) in remote and seismic/landslide activeу zones (bridge pillars, tunnel constructions, power lines structures, etc.).
A US-based semiconductor company asked Auriga to analyze and optimize Machine Learning and Deep Learning libraries’ performance on new processors.
Auriga developed web services for distributed monitoring and processing of data generated by wearable Holster EKG devices.
Auriga developed a drone software utility to monitor the condition of trees in an apple garden as a part of a big smart agriculture project.
A US-based leader in innovative technology solutions engaged Auriga to create an automated objects labelling and identification tool.
The most significant progress has been made in computer vision using convolutional neural networks, a class of deep neural networks applied to image analysis.
There are quite a few tasks in machine learning when the volume of the input data is small: unusual occurrences modeling, etc
The methods of automatic recognition with increasing accuracy require an increasing amount of tagged data for training and testing models.
Hilti POC contests are tech events where selected companies compete in solving real-world engineering and business challenges.