This visual assistant app helps blind users by generating image captions with Intel OneDNN and oneDAL reading them with Google text-to-speech library. Built using Streamlit and OneAPI toolkits, it extracts visual features and creates descriptions to provide greater awareness of surroundings.
Image segmentation of luxury cars, worked on the Intel OpenVINO notebook with Python, Matplotlib, training the model, uploading the photo, masking the photo, to change the image color.
We have developed an early warning system for student dropouts using Intel® AI Analytics Toolkits, specifically Intel® DAL and MKL. This powerful solution enables educational institutions to identify potential dropout risks early on by analyzing student data efficiently and accurately.
OORB introduces an open-source framework for building and teaching organic robotics, simplifying the journey from idea to prototype for all skill levels. Aimed at revolutionizing educational resources in advanced robotics, OORB supports coding in any language and offers an easy-to-navigate, modular
Welcome to TransData Rapid growth in the service and technology sectors and the heightened competition in the market have resulted in the need for businesses to increase productivity, integrate all available information, and improve the standard of customization.
Given that an instructor cannot supervise all students simultaneously, this system allows the instructor to receive alerts when students do not correctly complete the sequence of physical exercises.
Smart Kart uses IoT to reduce queues in malls with a smart cart. Products are automatically scanned and added to the bill when placed in the cart. No manual scanning, faster checkout. IoT enhances the shopping experience, minimizing queues, and satisfying customers.
The project develops smart glasses for visually impaired people, using IoT, AI, and OpenCV. The glasses connect to the internet, utilize AI for object recognition, provide audio instructions/alerts, offer navigation assistance, and support voice commands. Its goal is to enhance mobility&independence
This project aims to improve the quality of life for people with Alzheimer's disease and visual impairments, enabling them to maintain their independence and stay connected to their loved ones and important objects in their lives.
The project aims to use the Kaggle New Plant Disease dataset to develop a model that can accurately predict plant diseases using ResNet neural network architecture. The trained model will be converted to ONNX format and deployed on Azure Serverless Functions for efficient and cost-effective executio
Image classification for recycling refers to the use of machine learning to automatically classify images of waste materials into their respective categories. We have made use of Intel's oneAPI and its oneDNN library which provides highly optimized routines for various deep learning operations.
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.