There are 1 repository under inception-v3 topic.
Keras model of NSFW detector
A neural network to generate captions for an image using CNN and RNN with BEAM Search.
This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
⛵️ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]
Running Inception-v3 on Core ML
A system that takes food images as an input, recognizes the food automatically and gives the nutritional-facts as an output.
Image Recognition Model to detect plastics, glass, paper, rubbish, metal and cardboard. This is used to detect these pollution in the ocean to allow the eradication of these materials, helping marine life, fishermen, tourism and making the world resilient to climate change.
Dockerized Repo for "3D-PV-Locator: Large-scale detection of rooftop-mounted photovoltaic systems in 3D" based on Applied Energy publication.
Fully supervised binary classification of skin lesions from dermatoscopic images using an ensemble of diverse CNN architectures (EfficientNet-B6, Inception-V3, SEResNeXt-101, SENet-154, DenseNet-169) with multi-scale input.
Designed and Developed end-to-end scalable Deep Learning Project. It is a detection system trained using InceptionV3(CNN model) + GRU(Sequential model) model to classify a video as Real or Fake. Obtained the test accuracy of 89%.
Models Supported: Inception [v1, v2, v3, v4], SE-Inception, Inception_ResNet [v1, v2], SE-Inception_ResNet (1D and 2D version with DEMO for Classification and Regression)
🍊 :rice_scene: Orange3 add-on for dealing with image related tasks
This Repository Contains Solution to the Assignments of the Generative Adversarial Networks (GANs) Specialization from deeplearning.ai on Coursera Taught by Sharon Zhou, Eda Zhou, Eric Zelikman
This repository consists of our Final Year Project. You can find everything starting from our code to all the resources in this repository
Careium is an AI android application to help in having a long well-healthy life. Helps in tracking eaten food, ingredients, and nutrients. Careium has the advantage of estimating food ingredients, by getting food images using the mobile camera or uploading a pre-captured image to the application, resulting in related info of it such as Food’s Nutrition Components.
Image Retrieval in Digital Libraries - A Multicollection Experimentation of Machine Learning techniques
Inception V3 for Transfer Learning on Cats and Dogs
A simple image classification test using Core ML and Inception V3 model in Objective-C
Implemented a CNN-LSTM Action Recognizer for dynamic motion analysis, integrating convolutional and recurrent neural networks to efficiently recognize and classify actions in video data of UCF101 dataset.
InceptionV3-Multi-layer GRU based automatic image captioning with Keras and TensorFlow frameworks
This is an implementation of the paper "Show and Tell: A Neural Image Caption Generator".
In this repository you will find everything you need to know about Convolutional Neural Network, and how to implement the most famous CNN architectures in both Keras and PyTorch. (I'm working on implementing those Architectures using MxNet and Caffe)
My PyTorch implementation of CNNs. All networks in this repository are using CIFAR-100 dataset for training.
Deep image classification tool based on Keras. Tool implements light versions of VGG, ResNet and InceptionV3 for small images
A Convolutional Neural Network approach for image-based anomaly detection in smart agriculture
Deep Neural network using CNN pre-trained model to visually diagnose between 3 types of skin lesions
Automated pipeline for large scale detection of solar arrays in France
Classification of automotive parts as defective and non-defective with transfer learning.
Detected the crop diseases and differentiated between various crop diseases for a particular plant. Worked with appropriate neural network image classification algorithms like CNN, Inception-V3, VGG-16. and VGG-19
This repository contains the Jupyter Notebook for the InceptionV3 CNN Model trained on the Stanford Dogs Dataset.
metrics for generative models (fid, inception)
I explain how to export weights from a Keras model and import those weights in Keras.js, a JavaScript framework for running pre-trained neural networks in the browser. I show you later how to include the final result into a Phonegap Cordova mobile application.
Implementation of an Alzheimer's Disease detection system using Deep Learning on MRI images from a Kaggle Dataset.
Identification of road surfaces and 12 different classes like speed bumps, paved, unpaved, markings, water puddles, potholes, etc.
In this project work, the main motive is to build a deep learning model to detect air pollution from real-time images. In order to achieve that goal, we have collected data from different sources and then enhanced the low-quality images using the Image enhancement technique. Our next step was to train a CNN (Convolutional Neural Network) on the images in order to detect air pollution by analyzing the clearness of the sky in the image. In this work, we have used the Inception V3 model. After the successful testing of the CNN model, we have deployed the model on an Android Application.