mvronkin Goto Github PK

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-2023

ai-for-is-course

arch_comp_sys

lec, workshops, questions

asbest_veins_labeling

asbestos_labeling

basic_ml_alg

Supplementary repository for Basic Algorithms of ML in Python

cd-diagram

Critical difference diagram with Wilcoxon-Holm post-hoc analysis.

computer-vision-course_lec-practice

Курс Компьютерное зрение (глубокое обучение в компьютерном зрении) для баколавров 09.03.04 Программная инженерия

cvpytorch

CvPytorch is an open source COMPUTER VISION toolbox based on PyTorch.

deep-learning-in-image-processing-lectures

dsatools

Digital signal analysis library for python. The library includes such methods of the signal analysis, signal processing and signal parameter estimation as ARMA-based techniques; subspace-based techniques; matrix-pencil-based methods; singular-spectrum analysis (SSA); dynamic-mode decomposition (DMD); empirical mode decomposition; variational mode decomposition (EMD); empirical wavelet transform (EWT); Hilbert vibration decomposition (HVD) and many others.

for_course_dlcv

gost732

Преамбула и другие части LaTeX-документа для соответствия ГОСТ 7.32-2017

neural-networks-lectures-and-practice

operation-systems

passive-fingerprinting-of-same-model-electrical-devices-by-current-consumption

One of the possible device authentication methods is based on device fingerprints, such as software- or hardware-based unique characteristics. In this paper, we propose a fingerprinting technique based on passive externally measured information, i.e. current consumption from the electrical network. The key insight is that small hardware discrepancies naturally exist even between same-electrical-circuit devices, making it feasible to identify small variations in the consumed current. An experimental database of current consumption signals was collected. The resulting signals we classified within several modern time series classification methods, including \texttt{tsfel}, deep neural network (DNN), ROCKET and empirical wavelet decomposition-based manual feature extraction technique. We have successfully identified 40 similar (same-model) electrical devices with about 94\% precision.

sompy

A Python Library for Self Organizing Map (SOM)

stylegan2-pytorch

Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement

time-series-analysis-lectures-and-workshops

timeseriescourse