A Robotics, Computer Vision and Machine Learning lab by Nikolay Falaleev. The main focus of the blog is the application of Deep Learning for Computer Vision tasks, as well as other relevant topics: classical Computer Vision, Numerical Methods, and Hardware.
All of the blog post materials are available here.
A gold medal solution of the TGS Salt Identification Challenge.
Kaggle Challenge to segment salt deposits beneath the Earth's surface on seismic images.
How to increase inference speed on a semantic segmentation task and further ideas.
A CNN approach used for multiclass semantic segmentation during the Lyft Perception Challenge.
A partnered Lyft and Udacity semantic segmentation challenge with synthetic images.
An approach how to increase your position on a leaderpoard in a classification datascience competition by balancing predictions.
Ideas and approach to the Kaggle IEEE's Signal Processing Society - Camera Model Identification challenge.
A set of instruction to run a modern version of the deep learning framework TensorFlow on AMD Ryzen.
VGG16-based fully convolutional networks for semantic segmentation of images on Cityscapes
Application of a linear SVM for image classification with HOG, binned color and color histogram features.