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Found 9 papers, 4 papers with code
SAVOIAS: A Diverse, Multi-Category Visual Complexity Dataset
In this work, we introduce Savoias, a visual complexity dataset that compromises of more than 1, 400 images from seven image categories relevant to the above research areas, namely Scenes, Advertisements, Visualization and infographics, Objects, Interior design, Art, and Suprematism.
Scraping Social Media Photos Posted in Kenya and Elsewhere to Detect and Analyze Food Types
We also propose a scrape-by-keywords methodology and used it to scrape ~30, 000 images and their captions of 38 Kenyan food types.
Performance Comparison of Crowdworkers and NLP Tools on Named-Entity Recognition and Sentiment Analysis of Political Tweets
We report results of a comparison of the accuracy of crowdworkers and seven Natural Language Processing (NLP) toolkits in solving two important NLP tasks, named-entity recognition (NER) and entity-level sentiment (ELS) analysis.
Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System
In this work, we propose a video-based transfer learning approach for predicting problem outcomes of students working with an intelligent tutoring system (ITS).
Online Graph Completion: Multivariate Signal Recovery in Computer Vision
The adoption of "human-in-the-loop" paradigms in computer vision and machine learning is leading to various applications where the actual data acquisition (e. g., human supervision) and the underlying inference algorithms are closely interwined.
SIDOD: A Synthetic Image Dataset for 3D Object Pose Recognition with Distractors
We present a new, publicly-available image dataset generated by the NVIDIA Deep Learning Data Synthesizer intended for use in object detection, pose estimation, and tracking applications.
OpenFraming: We brought the ML; you bring the data. Interact with your data and discover its frames
The degree of user involvement is flexible: they can run models that have been pre-trained on select issues; submit labeled documents and train a new model for frame classification; or submit unlabeled documents and obtain potential frames of the documents.
Detecting Frames in News Headlines and Lead Images in U.S. Gun Violence Coverage
Such perspectives are called “frames” in communication research. We study, for the first time, the value of combining lead images and their contextual information with text to identify the frame of a given news article.
OpenFraming: Open-sourced Tool for Computational Framing Analysis of Multilingual Data
We propose and guide users through a five-step end-to-end computational framing analysis framework grounded in media framing theory in communication research.
