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.
DELIVERING OpenVino SOLUTIONS
Get valuable business insights from images, video and text using machine learning and computer vision OpenVino toolkit.
About
Industries
- Increase diagnostics accuracy for early abnormalities detection, reduce unnecessary procedures, improve image processing and health monitoring
- Prevent equipment failures, manage assets stock, check assembly faults, control manufacture process
- Improve driver’s safety with objects identification, monitor driver’s behavior, manage the fleet or enhance traffic control
- Get audience insights with demographic analysis, deliver meaningful visual search results, provide personalized shopping experience
- Explore crops wellbeing, control weeds, detect soil moisture or implement robotic-based harvesting
- Create secure experience with verified face recognition and video surveillance activity detection
Why Choose Auriga
Image processing, video objects detection, face recognition
With OpenVino, a framework mostly designed for convolution neural networks and deep learning inference, optimized for several Intel computational platforms, our engineers are ready to tackle any customer's challenge.
Hardware and embedded development adepts
Machine Learning requires immense computational resources. Benefit from 30+ years of hardware and embedded software development experience for an array of clients varying from technology software and hardware vendors, medical device, automotive, equipment manufacturers to telecom and service providers.
Machine Learning and AI-enhanced experience
Machine Learning Algorithms require extensive amount of training data. Training data may need to be organized, tagged and labeled. The data can be biased. We are experts in addressing, processing and managing all related tasks and issues.
Intel tech stack early adopters
Auriga’s engineers got profound experience with Intel© technologies adopting new cutting-edge platforms as soon as they reach the market. For example, we were one of the first companies to develop mobile solutions using Intel INDE featured at SF IDF forum.
Recent Projects
Technologies
Deep Learning Inference
- Intel CPU
- Intel FPGA
- Intel OpenVINO
- Intel® Movidius™ Neural Compute Stick
- Intel® Neural Compute Stick 2
- Intel® Media SDK
- OpenCV
- OpenCL
Related Frameworks
- Google TensorFlow
- MXNet (Apache)
- Caffe2
- Torch
Insights
Machine Learning Becomes Easier and Faster with OpenVINO
The most significant progress has been made in computer vision using convolutional neural networks, a class of deep neural networks applied to image analysis.
Neural Networks Application for Small-Scale Tasks
There are quite a few tasks in machine learning when the volume of the input data is small: unusual occurrences modeling, etc
ECG Rhythm Recognition by Deep Convolutional Neural Network
The methods of automatic recognition with increasing accuracy require an increasing amount of tagged data for training and testing models.
Auriga Presents Predictive Maintenance Model at Hilti POC Contest
Hilti POC contests are tech events where selected companies compete in solving real-world engineering and business challenges.