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Computer vision
Semantic and instance segmentation
Object detection and recognition
Multiple object tracking
Stereo vision
3D reconstruction and SLAM
Image retrieval
Pattern recognition
Machine learning
Dimensionality reduction
Fitting techniques
Clustering methods
Supervised ML
Neural networks
Feature crafting for CV problems
Deep learning
Face detection and recognition
Semantic segmentation
Monocular depth estimation
Human pose estimation
Multiple object tracking
Image recognition
Object detection and recognition
Image processing
Image enhancement
Image restoration
Image inpainting
Image segmentation and classification
Image-based steganography
Image compression
Image decomposition
Image filtering
Image editing
Signal processing
Biomedical signal analysis
Time-series analysis and forecasting
Sensor fusion (IMU, BLE, GPS, images, etc.)
Signal processing for AR/MR
Signal understanding, interpretation and filtering
Optimization of signal processing algorithms
Augmented & mixed reality
AR mobile SDKs
Optimized deep learning models for mobile platforms
Mobile image retrieval and visual search
Integration of custom C++ code on Android/iOS
TF Lite, Core ML, ML Kit for AI on
mobile
Web AR applications
Data
Optical imager
Infrared camera
X-ray images
Radar imagery
Platforms
Mobile
Web
Cloud
Embedded
01
Integration of high-quality solutions into various platforms and hardware
02
Extraction of information from visual data of any nature, sensors and conditions
03
Fusion of traditional approaches with different types of machine learning algorithms and deep learning architectures
04
Tailoring to the needs of businesses from different industries