Explore and run machine learning code with Kaggle Notebooks | Using data from Facial Expression Recognition(FER)Challenge. |
The dataset consist of disaster-related images from all over the world. Each image has been manually annotated by five different people with tags related to ... |
The best model was able to predict 5 emotions from images with 88% training accuracy and 70% testing accuracy. |
Explore and run machine learning code with Kaggle Notebooks | Using data from Facial Expression Recognition(FER)Challenge. |
503 open source sentiments images plus a pre-trained sentiment analysis model and API. Created by Irtika. |
This database contains a Visual Sentiment Ontology (VSO) consisting of 3244 adjective noun pairs (ANP), SentiBank a set of 1200 trained visual concept detectors ... |
Real-time face detection and emotion/gender classification using fer2013/IMDB datasets with a keras CNN model and openCV. |
The SST-5, also known as the Stanford Sentiment Treebank with 5 labels, is a dataset used for sentiment analysis. The SST-5 dataset consists of 11,855 single ... |
This section presents an overview of the most signif- icant works in the field of Image Sentiment Analysis published since 2010, when the first significant work. |
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