The model uses instance segmentation to classify the images into 4 classes sky, ground, small rocks, and big rocks denoted by grey, black, deep grey, and white.
Github repo:- (https://github.com/kuber2001/LunarModel_Oneapi)
This project aims to build an OneAPI-supported EEG-based BCI system for paralyzed patients to communicate with the world. With the help of EEG signals, this project decodes the words/speech thought inside the brain and identifies them with the help of machine learning models.
The goal of this project is to build a house prediction API by using the oneAPI machine learning frameworks; Scikit-learn, XGBoost, and an open VINO toolkit. To build and deploy my machine learning model in order to integrate them into other applications.
A used car price prediction ML project involves developing a machine learning model that can accurately predict the price of a used car based on various factors such as the car's make and model, age, mileage, condition, location, and other relevant features. The project typically involves collecting
The goal of this project is to build a One-Shot Face verification by collecting several images and saving them in the database as anchor images and then collect real-time images, both images are compared to give an output of either a True or False.
This project involves ETL and a Machine Learning Pipeline implementation, that classifies messages related to disaster response, and covering multiple language disasters, with a disaster emergency response using a Flask Web App.
Driver drowsiness is a severe issue that causes many road accidents every year. Drowsy driving can lead to accidents due to decreased reaction time, impaired decision-making, and impaired driving performance.
The students always tend to have the issue of figuring out which lift to use to reach their class floor at the peak hours. But to choose the optimal elevator could be worrisome and time consuming. But with the use of this AI/ML model that can figure out which lift to take to reach the desired floor
The Class Monitoring System using AI and ML technology is designed to monitor real-time student behaviour in the classroom. It provides teachers and school administrators with valuable insights into student engagement, attendance, and behaviour. This system is particularly useful in identifying stud
RespiScan 2.0 is a groundbreaking project aimed at enhancing lung cancer prediction through two innovative modes of analysis. Leveraging the power of Intel oneAPI, RespiScan 2.0 offers a comprehensive approach to early detection and prevention of lung cancer.
This is a heart disease prediction application which helps the doctors make informed decision about the heart disease of their patient’s. This application uses machine learning algorithms to analyse patient data and predict the likelihood of developing heart disease.
Implementation of a linear regression model and a neural network, two categories of machine learning models. We are utilising a dataset from the nutritional evaluations and constituents of several cereals.
Forest fires wreaking havoc and destroying several irreplaceable ecosystems is common news in the past few years owing to climate change. The best solution to the issue is having a reliable detection system, which can pick up on the early signs of a forest fire and inform the authorities immediately
The technology that we are proposing is a system that converts sign language to speech, allowing those who are deaf or hard of hearing to communicate more effectively with those who do not understand sign language.