er1009's repositories
plant-disease-detection
This project deals with the development of a basis for an artificial intelligence-based system for monitoring the condition of the cannabis plant. The goal of the system is to provide a real-time for identifying diseases/deficiencies in cannabis plants. At the core of the system are neural-network-based models, that allow monitoring on the condition of the plant using an image
build-conv-layers-and-perform-experiments
implement from scratch, a forward path of a convolutional layer and experiment with it
Language:Jupyter Notebook000
Language:Jupyter Notebook000
Create-Dataset-Bing-Rekognition-TrainYolov5-docker-flask
create object detection data set from scratch using azure Bing api and AWS Rekognition, train a yolov5 model using ultralytics DOCKER, and infer the model on flask rest-api.
Language:Jupyter Notebook000
Language:Jupyter Notebook000
Language:Jupyter Notebook000