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CV Team
Team delivers the methods of Computer Vision and Deep Learning
BUSINESS CASES
Dataset Processing (augmentation, distillation, etc)
CV pipeline inference and training optimization
Photo- and Video-based processing pipelines creation
TASKS CLASSES
Image/Video сaptioning, Keypoints Detection&Tracking
Generative models such as GAN, AutoEncoders, etc
Neural Architecture Search & SuperNets
Zero-shot approach
Img2img architectures such as PyNet
CURRENT CHALLENGES
Zero-shot methods for solving the main part of CV problem statement such as img2img
Decrease of data needed for training the CV methods
SotA models usage in real processes for improving the business metrics
ACHIEVEMENTS
50% decrease of dataset volume needed for image classification problem statement
Clients Cases
MIL Team Research - CV Team
Full Automation of neural networks search process for classification problem statements
Clients Cases
MIL Team Research - CV Team
30% better cells segmentation in the table processing task while Documents recognition
Clients Cases
MIL Team Research - CV Team
Improving the quality of SuperNets training process by several times
Clients Cases
MIL Team Research - CV Team
10-time decreasing of GPU resources while ranking architecture due to the quality in evolutionary NAS methods
Clients Cases
MIL Team Research - CV Team
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