Implementing Transfer Learning using Resnet18. Training and testing Resnet18 on Even numbered Classes in CIFAR10 Dataset.
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Updated
Jun 8, 2024 - Jupyter Notebook
Implementing Transfer Learning using Resnet18. Training and testing Resnet18 on Even numbered Classes in CIFAR10 Dataset.
Pneumo.ai is a Streamlit web app for detecting pneumonia from X-rays, leveraging CNN variants like AlexNet, VGG, and ResNet18, with ResNet18 leading with an accuracy of 0.89. It employs early stopping callbacks for efficient model training, visualizes training using TensorBoard, and optimizes inference time with pruning and quantization techniques.
CNN-based classifiers for classifying audio samples into 13 distinct categories, such as laughter, car horn, dog bark, etc.
Проект ML/DL определения сердечной недостаточности по векторной электрокардиографии
EthnicityPredictor-UTK is a PyTorch-based project that focuses on predicting ethnicities from facial images using state-of-the-art ResNet architectures. Leveraging the UTKfaces dataset, the model is trained to recognize diverse facial features and make accurate ethnicity predictions.
A pre-trained image classifier to classify dog breeds. Udacity Nanodegree project-1.
Efficient and Lightweight Ear Segmentation AI Model
Convolutional Neural Network for Face Recognition
HAM10000 Skin Lesion Classification
Light-weight Single Person Pose Estimator
Automated Wildlife Monitoring Using Deep Learning
Using the GTZAN dataset to create a classifier that can classify what the music genre is playing!
Financial Time Series Forecasting using Deep Learning Techniques and Innovative Image Encoding Approaches
A Flask app for handwritten digit prediction.
Resnet-18 from scratch, using Pytorch
Leaf Disease Detection: A project enabling farmers to identify plant diseases by scanning leaves, providing brief descriptions and suggesting supplements for treatment.
PyTorch implementation of Conditional Generative Adversarial Networks (cGAN) for image colorization of the MS COCO dataset
Text analysis using text-to-image conversion and deep neural models trained for image processing
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