Computer vision [Discussion]
In the discussion, we’re going to talk about the current state of Computer Vision, difficulties and tricks on the way of creating ideal products in CV, long-tail issue, performance issues, product features interpretation for users. It should be interesting for data scientists, engineers, product managers, product owners.
Vote and propose your topic here - https://app.sli.do/event/hnnmthu5/live/questionsModerator: Alex Lazarev (Research Engineer @ Ring Ukraine)
- Igor Krashenyi (Sr. Research Engineer @ Ciklum
- Alexander Onbysh (Research Engineer @ Ring Ukraine)
- Kyryl Truskovskyi (Neuromation)
- Oles Petriv (Head of R&D @ NeoCortext and VideoGorillas)
- Sergey Kuprienko (GM Research @ Ring Ukraine)
- Kyryl has over 7 years of experience in the field of Machine Learning
- He currently holds the position of MLSE (machine learning software engineer) in the Canadian company BorealisAI
- For the bulk of this career, he has helped build machine learning startups, from inception to product.
- He has also developed expertise in choosing and implementing state of the art deep learning architectures and large-scale solutions based on them.
- Twitter, GitHub
- Head of Research
- Specialized in: CV, Deep Learning/Machine Learning (objects classification, motion detection, segmentation, GANs etc.)
- Sphere of interests: AI, Video Games, Music, Yoga, Table Tennis
- Computer Vision Research Engineer @ PiñataFarms
- PhD in Biological and Medical Candidate of Science in Biological and Medical Devices and Systems
- Specializes in Deep Learning for computer vision tasks
- He is fond of machine learning competitions, Kaggle Master
- Head of ML Pipelines
- Main field of interest is high-load distributed systems. Has decent experience in production CV pipelines with real-time video stream processing. Was working on developing motion detection, object detection, face recognition pipelines.
- Specialized in CV/DL, system architecture, video streaming, performance optimizations.
- GitHub, LinkedIn
- Head of R&D @ NeoCortext and VideoGorillas
- For the last 7 years he has been actively researching and developing computer vision systems and natural language processing
- The author of a Prometheus online training course and an ARVI Lab machine learning course
- Directed the development of projects in the automated analysis of news in different languages, the recognition of named entities, the analysis of conceptual drift and the representation of language structures using machine learning systems
- During this year, he has been working on the Reflect.tech system for automatically transmitting human facial features, as well as the task of splitting 4x video resolution for movie studios at VideoGorillas
- Youtube, Facebook
- GM of Research @ Ring Ukraine
- Leads Research division of Ring, the smart doorbell company
- He was building CV and text recognition systems running on ARM