Python library to fetch image urls based on keywords and download from Bing.com.
-
Updated
Jun 15, 2023 - Python
Python library to fetch image urls based on keywords and download from Bing.com.
PyTorch implementation of "Dynamic Structure Pruning for Compressing CNNs" (AAAI 2023 Oral)
CNN Image classification of trash of 6 categories in tensorflow and pytorch
Image Classification on CIFAR-10 using Theano
learning data science including languages Python and SQL, data visualisation and machine learning
Using CNN for classifying dogs and cats images
Diagnose - Skin cancer detection from your skin images.
Deep Learning - Portability and optimization of a neural network for rapid damage detection in earthquakes using OpenVINO toolkit
The purpose of this project was to simply test a CNN model on a competition FER2013 dataset.
Finetuned pretrained-CNN architectures on Kaggle's FGVC21 plant pathology dataset (Implemented in Keras)
This project is an image classification project using a deep-learning based on Convolutional Neural Networks (CNNs) with Keras. The Dogs vs. Cats is a classic problem for anyone who wants to dive deeper into deep-learning.
Explores the use of a simple CNN model for the detection of COVID-19 in X-ray images. Leveraging a dataset from Kaggle, the pipeline includes preprocessing, model architecture design, performance evaluation, and testing on new cases.
The project includes a detailed explanation of the CNN and ICP algorithms, along with their implementation in Python using popular deep learning and computer vision libraries such as TensorFlow, Keras, and OpenCV. The dataset used for training and testing the models is the CIFAR-10 dataset, which consists of 60,000 32x32 color images in 10 classes.
This project consists of following steps: - dataset creation with web scraping (BeautifulSoup) - data pre-processing (DifPy, Rembg, Keras) - CNN deep learning model training (used MobileNet V2 model) and training (Tensorflow) - testing the model and analyzing the results.
Build end-to-end DL pipeline for computer vision (Image classification) for “Chest Disease Classification from Chest CT Scan Images” and deploy Flask web app to AWS EC2 with Docker and CI/CD tool: Jenkins
Android app that identifies UT and UTD landmarks
Add a description, image, and links to the cnn-image-classification topic page so that developers can more easily learn about it.
To associate your repository with the cnn-image-classification topic, visit your repo's landing page and select "manage topics."