Sep 25, 2023
Data Imputation using Reverse ML
Abstract Imputation fixes broken data. Methods are from making it constant mean to clustering, regression and generative networks. What if...
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All engines Anomaly Detection Computer Vision Natural Language Processing Other Prediction Systems Recognition and Classification Text Analysis Time Series Forecastings
Sep 8, 2023
Researching Visual Question Answering: Bridging the Gap between Humans and AI
Introduction The goal of this project is to offer regular users and developers the chance to engage in practical visual...
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Jul 16, 2019
Differentiable Programming – Inverse Graphics AutoEncoder
Intro to Differentiable Programming DeepLearning classifier, LSTM, YOLO detector, Variational AutoEncoder, GAN – are these guys truly architectures in sense...
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Jun 14, 2019
Point Cloud Data: Simple Approach
Introduction to Point Cloud Data In recent years, there was great progress in the development of LIDAR detectors that resulted...
Read more ❯Nov 12, 2018
Active Learning on MNIST – Saving on Labeling
Active Learning is a semi-supervised technique that allows labeling less data by selecting the most important samples from the learning process (loss) standpoint. It can have a huge impact on the project cost in the case when the amount of data is large and the labeling rate is high. For example, object detection and NLP-NER problems.The article is based on the following code: Active Learning on MNIST (more…)
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May 16, 2018
Vectorization of Raster to Polygons
Vectorization of Raster We would never start writing any vectorization code if there was any free library. However, recently Andy...
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Oct 16, 2017
The Natural Ear for Digital Sound Processing – as an alternative to the Fourier Transform
Fast Fourier Transform (FFT) in Digital Sound Processing This is a primitive prototype of the natural ear. Why I came...
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