Ivan Ye. Zhovannik's repositories
simple-async-openai-assistant
Asynchronous FastAPI wrapper for AsyncOpenAI and OpenAI assistantAPI Resources
source-infuser
This package prepares your software project for continuous injection into your AI assistant
MilkHeatTreatmentEvaluation
A readily available, fast, non-destructive front-face fluorescence technique is used as a tool for assessing heat treatment effects on milk. Spectral data on raw, pasteurized, UHT pasteurized and sterilized milk samples from a wide range of manufacturers are obtained, including reconstituted milk and its mixtures with pasteurized milk. The principal component analysis (PCA) is used to summarize all the data obtained, and a classification model is developed to distinguish between two classes of milk (1) raw and pasteurized milk and (2) milk that was exposed to high heat treatment (UHT pasteurization or sterilization), or contains products of such a treatment (dry milk). A validation procedure using a test set showed the model to be accurate to within less than 5%. A new spectral index for use in the present context, which uses the ratio of the vitamin A and Maillard reaction products peaks in fluorescence excitation spectra, is proposed and compared with the conventional FAST index.
convert_caffe_windows
Convert caffe to tensorflow for Windows using Docker
caffe-tensorflow
Caffe models in TensorFlow
docker-python
Kaggle Python docker image
ivanzhovannik
Biography
radiomics_correction_CTSNR
The files supporting radiomics correction paper will be places here