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EEG_Classification_Deeplearning
EEG Signal Classification using LSTM on various datasetsSmileToCast-Blender
Blender console easily convert dentist planning smile to 3D printable customized cast for veneers \ or cosmetics procedure planning .. Cast to be then scaled to real size impression.Health_Discernment_System
An efficient and user-friendly application with GUI based (Tkinter) front-end and various custom CNN models as back-end which detects various human diseases such as Malaria, Pneumonia, Breast Cancer and Skin Cancer using cell, tissue, x-ray or skin images.Android-Cholesterol-Checker
Android-Application-Cholesterol-Checker in Javaanatomic-implants
OnlineDentalClinic-AndroidApp
2048-console
A clone of the game 2048 in the console written in vanilla python without any imports.Julia-Knaspsack
Knapsack is a problem in dynamic programming who try to get the best option to takeVehicle-Detection-Image-Set
MONAI-3D-Pelvic-Bone-cancer-segmentation-and-classification
Author : Bashar Shami , [email protected] Team: Mona ShoumanGymManagement
A java swing Gym Management project that consists of three types of user logins--Admin, Manager, Customer.Intelligent-Estimation-of-Speed-of-Induction-Motor
speed tracking capability of model reference adaptive system (MRAS) with model-based flux/speed observers and artificial neural network (ANN)-based adaptive speed estimators for sensorless induction motor (IM) drives has been analyzed. In model-based technique, mathematical model of IM is used to estimate the rotor speed. The current and flux observers are used as the reference model to estimate the rotor flux. The estimated rotor flux signals are used as the input signal for the adaptive observer to estimate the speed. In ANN-based method, adaptive model is constructed with a feedforward neural network to estimate the rotor speed. Feedforward ANN algorithm is used to train the network. The training algorithm decides the learning speed, stability, and dynamic performance of the system. Both methods have good speed tracking capability. Simulation results are presented to know the accuracy of the proposed methods. The proposed speed estimation techniques have great potential in industrial applications.Love Open Source and this site? Check out how you can help us