Light-weight Single Person Pose Estimator
-
Updated
May 3, 2024 - Jupyter Notebook
Light-weight Single Person Pose Estimator
Towards deepfake detection that actually works
An easy implementation of Faster R-CNN (https://arxiv.org/pdf/1506.01497.pdf) in PyTorch.
An easy implementation of FPN (https://arxiv.org/pdf/1612.03144.pdf) in PyTorch.
ROS 2 packages for PyTorch and TensorRT for real-time classification and object detection on Jetson Platforms
基于tf.keras的多标签多分类模型
This project is about detecting defects on steel surface using Unet. The dataset used for this project is the NEU-DET database.
Multi-label defect detection for Solar Cells from Electroluminescence images of the modules, using Deep Learning
Code and example data repository for Mommert (2020): Cloud Identification from All-sky Camera Data with Machine Learning, Astronomical Journal, 159
Post-training static quantization using ResNet18 architecture
Implementation of "Cost-Effective Active Learning for Deep Image Classification" paper
Train ResNet18 on AFAD dataset for gender and age estimate with Pytorch
Fight Detection From Surveillance Cameras by fine-tuning a PyTorch Pretrained Model
Classifying the type of property given Real Estate, satellite and Street view Images
Collection of tensorflow notebooks tutorials for implementing some basic Deep Learning architectures.
This project uses Deep learning concept in detection of Various Deadly diseases. It can Detect 1) Lung Cancer 2) Covid-19 3)Tuberculosis 4) Pneumonia. It uses CT-Scan and X-ray Images of chest/lung in detecting the disease. It has a Accuracy between 50%-80%. It can take input in any Image format or through Live videos and provide accurate output…
Classify ECG signals into predefined categories based on heartbeat abnormality by transforming time series to images
Efficient and Lightweight Ear Segmentation AI Model
A simple TensorFlow 2 implementation of ResNet-18
Add a description, image, and links to the resnet-18 topic page so that developers can more easily learn about it.
To associate your repository with the resnet-18 topic, visit your repo's landing page and select "manage topics."