oneAPI

Deliver uncompromised performance for diverse workloads across multiple architectures.

VeriFusion-Unmasking Synthetic Realities in Audiovisual Streams.

URL: https://github.com/Amar1701/deepfake_detection

Description:

Our project Efficiently trained with Intel® oneAPI: oneDAL, our Deep Learning Model enhances deepfake detection, ensuring robustness and accuracy. This agile approach offers superior protection against evolving threats in manipulated multimedia content.

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Sexual Harassment Detection in Workplace

URL: https://github.com/Altaf-01/Sexual-Harassment-Detection-In-Workplace

Description:

Sexual harassment in workspace has become a serious issue nowadays. Our solution is an attempt to build a safer environment. We have developed 3 CNN-based models to detect this issue, complete CNN model, VGG16 model, Xception model. Out of which VGG16 gained us a maximum accuracy of 92%(approx.)

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Pothole Detection Showdown: YOLOv7 Native vs. Intel OneAPI

URL: https://github.com/Ragulprince/openvino-yolov7

Description:

Project Description: In this project, we conducted a head-to-head comparison between two powerful object detection approaches, YOLOv7 native and Intel OneAPI Libraries, in the context of pothole detection. 🕳️ 📌 Objective: Our goal was to determine which approach offered the best trade-off between

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Solar Flares Prediction / Unsupervised Learning

URL: https://github.com/SHIVAANISREE/SolarFlares

Description:

Predicting solar flares is of critical importance for mitigating the potential adverse effects of these intense bursts of radiation on power grids, GPS systems, and the safety of individuals in space. Intel OneAPI is powerful tools can play a pivotal role in building solar flares prediction systems.

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Water quality prediction

URL: https://github.com/Subharanjana2/Water-Quality-Prediction-Intel-OneAPI-Hackathon/blob/adb1a2017c0c610c047434f32b3251e98f806ee2/README.md

Description:

, we can evaluate the quality of water based on a range of crucial parameters, allowing us to make informed decisions about its fitness for human consumption. The suggested solution offers comprehensive exploration of various machine learning models and techniques applied to this dataset. From

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Prediction & Detection of Human Fertility

URL: https://github.com/DharaniDharan0109/Hack2skill-Intel-OneAPI-Hackathon-AI-Analytics-toolkits-Human-fertility

Description:

Firstly, it is a multi-modal dataset containing different data sources such as videos, biological analysis data, and participant data. Secondly, it is the first dataset of that kind in the field of human reproduction. It consists of anonymized data from 85 different participants.

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