Sign Language Recognition Project using OpenCV Python Sign Language Recognition using Machine Learning, In this project it works on Sign to Text Conversion Project, ML model is trained on large dataset of images of word (i.e., call, good, hello, house, no, ok, etc.). User have to show the exact sign of word from hand gesture […]
Sign Language Recognition Project with Source Code Sign Language Detection and Sentence Suggestion leverage neural networks to interpret and understand sign language gestures. This application translates sign language into text or speech, facilitating communication between individuals with hearing impairments and those who do not know sign language. The neural networks’ proficiency in recognizing diverse sign
Sign Language Recognition and Gesture Generation System Sign Language Recognition and Gesture Generation System designed to bridge communication gaps between hearing-impaired and non-impaired individuals. Sign Character Recognition via MediaPipe landmarks with CNN+LSTM architecture, and a sign generator that converts text input into sign language visuals. Natural Language Processing techniques enhance prediction accuracy by providing contextual
Sign Language Recognition and Gesture Generation System Sign Language Recognition using CNN | Machine Learning Projects Sign Language Recognition and Gesture Generation System designed to bridge communication gaps between hearing-impaired and non-impaired individuals. The system incorporates multiple modules: gesture recognition using YOLOv8, sign character recognition via MediaPipe landmarks with CNN+LSTM architecture, and a sign generator
Sentiment Analysis on Reviews with Neural Networks Sentiment Analysis on Reviews utilizes neural networks to analyze and interpret sentiments expressed in product or service reviews. This application processes textual content to determine whether reviews are positive, negative, or neutral, providing valuable insights for businesses and consumers. The neural networks’ ability to understand context and nuances
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Traffic Sign Detection for Self Driving Cars using Computer Vision Self-Driving Car Project using Machine Learning, In this project user can upload image or videos to ML model and it will detects road lane, traffic signs and autonomous steering according to curve. Simultaneously it will identify the person drowsiness state and it works on real-time.
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Road Pothole Detection using Deep Learning Pothole Detection and Road Segmentation using ML, aim of this project is to develop a deep learning-based system to detect and segment roads and potholes from images and videos. The project involves the use of semantic segmentation models trained on specific datasets to identify road areas and potholes, overlaying
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Multiple Eye Disease Detection Using Deep Learning Retinal diseases such as diabetic retinopathy, glaucoma, and age-related macular degeneration are leading causes of blindness worldwide. Early detection and treatment of these diseases are crucial for preventing vision loss. This project aims to develop an automated retinal disease detection system using machine learning algorithms to analyze fundus
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Eye Disease Detection using OpenCV Python Diabetic Retinopathy Disease Project aims to develop an intelligent system for automated detection of retinal diseases from fundus images using deep machine learning algorithms. The system is implemented in Python using the Tkinter module for building the graphical user interface. A deep residual neural network (ResNet) is trained on
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Diabetic Retinopathy Detection Retinal image analysis using machine learning and computer vision techniques has been an active research area over the past two decades. The emergence of deep learning has significantly advanced the automation of medical image analysis and disease detection. Retinal Diseases such as diabetic retinopathy, glaucoma, and age-related macular degeneration are leading causes
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