Position: Computer Vision Engineer
Category: Data Science
English level: upper
Years of experience: 3


Project description 
Landslide detection and bare rock segmentation using Landsat multispectral images, DEM data from LIDAR and HR data from GeoEye1, WorldView3. 
Designed and implemented models for bare rock segmentation (UNet, SegNet, CNN, ReSeg, ResNet), pixel-based classification and object-based classification (unsupervised segmentation + feature extraction + classification using RF and SVM)
Extracted feature (from DEM data): curvature, TPI, geomorphons, texture, roughness, etc. 
Prepared and published a paper in Remote Sensing Journal 

Project description 
Shopping Chatbot (StyleHacks). Chatbot for an iterative search of a product with a query refinement.
Trained models for word embeddings (LSTM, ELMO, BERT) 
Implemented model for semantic search (text to image) (DeVISE)
Implemented model for sentence structure analyzing and splitting complex sentences

Project description 
Recommender system for fashion and clothes sketch generation.
Designed models for clothes sketch generation (Genetic algorithm, GAN).
Design models for sketch generation using key points and user body measures

Project description 
House window detection for online blurring. 
Designed models for house window detection (Hough Transform + classification using CNN, HOG + SVM, Haar cascades, YOLO, SSD, MobileNet)
Technologies
Python.

Project description 
Prediction of air pollution in Kryvyi Rih based on 5-year data.
Designed models for anomaly detection,
Designed models for forecasting of air pollution (ARMA, ARIMA, SARIMAX)
Tricky tasks
Comfortable offices  within walking distance from a subway station
Flexible working hours