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age-macular-disease-detection

Age-Related Macular Disease Detection Using CNN: Employing Convolutional Neural Networks to identify and diagnose age-related macular degeneration swiftly and accurately.

alert-drowsy-driver-with-opencv

A computer vision system that monitors driver's facial features and eye movements in real-time. If signs of drowsiness are detected, the system issues immediate alerts, enhancing road safety by preventing potential accidents due to driver fatigue.

algorithm-visualizer

Algorithm Visualizer is a tool where you can see how different computer algorithms work. It shows animations of each step, making it easier to understand concepts like sorting data, searching through information, and navigating through graphs. This tool is great for students, teachers & anyone curious about learning algorithms in an interactive way

chatbot-using-ml-nlp

Conversational chatbot leveraging Machine Learning (ML) and Natural Language Processing (NLP) for dynamic interactions. Seamlessly integrated with a front-end framework for an intuitive user interface, enabling responsive and context-aware conversations.

classifying-brain-tumor

Classifying Brain Tumor Using CNN: A deep learning technique that employs Convolutional Neural Networks to accurately identify and categorize brain tumors in medical images.

classifying-the-types-of-flowers-using-cnn

Flower type classification with Convolutional Neural Networks (CNNs) involves using deep learning to analyze image patterns, enabling automatic identification of different flower species based on distinct visual features.

color-identification

Color identification in an image using machine learning involves the automated recognition and labeling of distinct colors present in a given image, enabling various applications like object detection and image analysis.

detection-of-retinal-pigmentosa-in-paediatric-age-patients-using-cnn-with-tkinter-framework

Revolutionizing pediatric retinal disease diagnosis, our innovative approach employs Convolutional Neural Networks (CNN) integrated with Tkinter framework for swift and accurate detection of Retinal Pigmentosa in young patients, ensuring early intervention for better outcomes.

dog-breed-identification-using-cnn

Dog Breed Identification Using Convolutional Neural Networks involves training a computer model to analyze images and classify dogs into specific breeds. Leveraging deep learning techniques, the system learns distinctive features, enabling accurate breed identification from input images.

droid-voice-control-hub

Droid revolutionizes human-computer interaction by serving as an all-encompassing hub for touchless control. Harnessing cutting-edge Machine Learning and Computer Vision, it seamlessly interprets hand gestures and voice commands, eliminating the need for direct contact. Experience a new dimension in intuitive computing on the Windows platform.

easyocr

Developing a Smart Selfie project using OpenCV and machine learning, where advanced algorithms enhance facial features for optimal selfies, demonstrating the fusion of computer vision and artificial intelligence in image processing.

facial-eye-detection-of-a-person

Facial and eye detection is a computer vision technique that identifies and locates faces and eyes within images or real-time video streams. It employs algorithms to analyze facial features, enabling applications such as security surveillance, biometrics, and emotion recognition.

fake-news-classification-

Fake News Classification: Utilizes Naive Bayes for traditional text data and LSTM for sequential text analysis to discern between real and fake news articles with high accuracy

future-stock-trend-estimation-using-lstm

Future Stock Trend Estimation utilizes Long Short-Term Memory (LSTM) for predictive analysis. The model is deployed on a Streamlit Application, providing real-time insights into stock market trends with dynamic visualizations.

heart-disease-detection

Machine learning detects heart disease by analyzing medical data for early diagnosis and intervention, improving patient outcomes."

helmet-detection

Don't Break Traffic Rules: Detects helmets and extracts number plates from images/videos using advanced computer vision technology for safer roads.

identifying-defects-in-various-fabric-using-cnn

Detect fabric defects with precision using CNN in this project, ensuring product quality and reducing manufacturing errors.

identifying-weight-category-of-person-using-random-forest

"Identifying weight categories using Random Forest involves leveraging machine learning to analyze various features and predict a person's weight class. This classification method enhances accuracy by combining multiple decision trees, offering a robust and efficient solution for weight categorization."

it-log-analyser

kidney-stone-detection-using-transfer-learning

Kidney Stone Detection employs Transfer Learning, a machine learning technique, to enhance accuracy. By leveraging pre-trained models, it swiftly identifies and classifies kidney stones in medical imaging, streamlining diagnosis for efficient treatment.

lane-identification-system

Lane identification is a system that determines the specific lane a vehicle is traveling in. Using sensors and computer vision, it enhances traffic management and assists autonomous vehicles in navigating safely within designated lanes.

license-plate-recognition

License Plate Recognition (LPR) is a technology that uses optical character recognition to automatically read and interpret license plate information from images or video feeds. Widely employed in security, parking management, and law enforcement, LPR enhances efficiency by swiftly identifying and tracking vehicles.

movie-recommender-system-application

A user-friendly application powered by Streamlit, offering personalized movie recommendations based on user preferences, enhancing the movie-watching experience with tailored suggestions.

mudassiruddin7

mudassiruddin7.github.io

multiple-disease-prediction-system

Multiple Disease Prediction System employs machine learning algorithms on medical data for early diagnosis. Utilizing predictive models, it assesses risk factors to provide timely and accurate predictions, aiding in proactive healthcare interventions.

music-genre-identification

To analyze audio features and classify songs into distinct genres, enabling automated and accurate genre tagging for a seamless music listening experience.

next-word-prediction-with-nlp-deep-learning

Next-Word Prediction with NLP and Deep Learning leverages advanced language models to anticipate the succeeding word in a sentence. Through neural networks and contextual analysis, this technology enhances text generation, fostering more intuitive and efficient communication in various applications.

object-detection-yolov3

The Object Detection YOLOv3 project employs the YOLO (You Only Look Once) algorithm's third version to swiftly and accurately identify and locate multiple objects within an image or video stream, making it an efficient solution for real-time object detection in various applications such as surveillance, autonomous vehicles, and image analysis.

pothole-detection

Roadside Pot-Hole Detection using Transfer Learning In order to improve road safety, an AI-driven system called ResNet-50 uses the deep learning model ResNet-50 to identify and alert authorities about potholes in the Road.