conv networks to identify objects within images (classification + identification)

This project aims to detect pneumonia from chest X-ray images using a Convolutional Neural Network (CNN). The model is trained on a dataset of chest X-ray images and evaluated for its performance. The project is ongoing, and I aim to fine-tune the model in the future. If you are seeing this, it means I am still working on the project.

circle detection using cnn

This tutorial shows how to classify images of flowers using a tf.keras.Sequential model and load data using tf.keras.utils.image_dataset_from_directory. It demonstrates the following concepts: Efficiently loading a dataset off disk. Identifying overfitting and applying techniques to mitigate it, including data augmentation and dropout.

YOLO (You Only Look Once) is a real-time object detection system that can detect objects in images and videos quickly and accurately. The deep learning algorithm is trained to recognize new objects and improve its accuracy over time.

If you want to understand how CNN(resnet50) works layer by layer. you at the right place.

This project is used to identify the fake vehicle by using number plate and face recognition . Problem statement provided by KAVACH HACKATHON 2023 PSID = KVH-005

This code trains a CNN in Keras to classify cell images (infected/uninfected). It sets up data generators, defines model architecture with convolutional layers, applies regularization, configures callbacks, and trains the model for binary classification.

Fine-tuned EfficientNetV2B0, for binary Image_Classification, with Gradio.

An emotion detection CNN-based model that can detect emotions from images in real-time

Ear segmentation in real time

A scalable, Fully Homomorphic Encryption (FHE) pipeline that allows for model inference on encrypted data without the need for decryption.

An application built with TensorFlow and Keras for traffic sign detection. Utilizes Convolutional Neural Networks (CNNs) to accurately identify and classify traffic signs from images. Achieved an accuracy of 98.89% on the test dataset. Simply upload images to classify traffic signs. Contributions welcome!

Proposing a novel machine learning-based approach for real-time suspicious activity detection in surveillance videos to enhance public safety and prevent terrorism, theft, accidents, and criminal activities.

Project that detects the brand of a car, between 1 and 49 brands, that appears in a photograph, with a success rate of more than 70% (using a test file that has not been involved in the training as a valid or training file, "unseen data") and can be implemented on a personal computer

Lung Cancer Prediction Model: Leverage the power of deep learning with this TensorFlow-based project. Trained on a dataset of lung X-Ray images, the model accurately predicts cancer cases. Easily integrate and utilize the model for early detection. #HealthTech #MachineLearning

morse code to text converter using CNN model

TensorFlow Image Classification App 🖼️

People Counter machine helps to track the people with the unique specifications and manages the data

Object Detection with CNNs, ViT, and YOLO