MACHINE Anomaly detection
Unsupervised learning based data sampling learning modeling and key feature extraction
Development of an optimal decision boundary search algorithm for classifying and determining normal or abnormal features
Improvement of transfer learning model
Sound recognition & generation
(CNN +)deep learning modeling to build superb audio classifier/generator to recognize every sound
Deep Learning-based generative & discriminative modeling
Object detection & recognition
Reliable object detection and recognition help robots to react adequately for quickly adapting to changes
General object(e.g. car) or robotics (e.g. skeleton) real-time detection & tracking
Multi-modal Data analysis
Multi-modal data analysis including emotion detection, heterogeneous data convergence make robot to diagnose current status with prediction
Raw source data (IoT, text, image, video, etc.) identifier management and status monitoring with ensemble approach
Cooperation Process to build A.I solution for You
1. Needs summary and pre-analysis experiment from R-SPIRIT based on research
2. Proposal to go to next step for realization
3. Co-working with data collecting-preprocessing-analysis-testing
4. Cyclic improvement by continuous market monitoring for launch