From ae3322ea42fe1e6f599a028cfec5376d39ef3362 Mon Sep 17 00:00:00 2001 From: ARYAHARIDAS06 <115702468+ARYAHARIDAS06@users.noreply.github.com> Date: Tue, 11 Jun 2024 21:29:58 +0530 Subject: [PATCH] Update aryamolvh@mulearn.md --- profiles/aryamolvh@mulearn.md | 10 ++-------- 1 file changed, 2 insertions(+), 8 deletions(-) diff --git a/profiles/aryamolvh@mulearn.md b/profiles/aryamolvh@mulearn.md index 0b7d1f816..06328d737 100644 --- a/profiles/aryamolvh@mulearn.md +++ b/profiles/aryamolvh@mulearn.md @@ -10,14 +10,8 @@ ### My Projects | Name | Description | Hosted Link | Repo Link | |---------------------|---------------------------------------------------------------------------|------------------------------------------|----------------------------------------------------------------| -| **DEEP FAKE Detection -using machine learning** | Developed a deep fake image detection system utilizing Machine Learning techniques. - Trained a model using VGG-16 on a dataset of authentic and manipulated images. - Implemented a Flask-based web application for user interaction and real-time image analysis - Integrated the ML model to classify images and identify potential deep fake content. | [Host | | -| **Real-time Drowsiness Detection in Drivers (CNN)** | Utilized computer vision techniques to analyze facial features and eye movements for signs of drowsiness. - Trained the model on a dataset containing images of alert and drowsy drivers, achieving. - Implemented the model using Python and OpenCV for video stream processing | | | +| **DEEP FAKE Detection using machine learning** | Developed a deep fake image detection system utilizing Machine Learning techniques.Trained a model using VGG-16 on a dataset of authentic and manipulated images.Implemented a Flask-based web application for user interaction and real-time image analysisIntegrated the ML model to classify images and identify potential deep fake content. | | | +| **Real-time Drowsiness Detection in Drivers (CNN)** | Utilized computer vision techniques to analyze facial features and eye movements for signs of drowsiness.Trained the model on a dataset containing images of alert and drowsy drivers, achieving.Implemented the model using Python and OpenCV for video stream processing | | | #### Leadership and Influence: