GRIFT: A graphical model for inferring visual classification features from human data
نویسندگان
چکیده
This paper describes a new model for human visual classification that enables the recovery of image features that explain human subjects’ performance on different visual classification tasks. Unlike previous methods, this algorithm does not model their performance with a single linear classifier operating on raw image pixels. Instead, it represents classification as the combination of multiple feature detectors. This approach extracts more information about human visual classification than previous methods and provides a foundation for further exploration.
منابع مشابه
Palarimetric Synthetic Aperture Radar Image Classification using Bag of Visual Words Algorithm
Land cover is defined as the physical material of the surface of the earth, including different vegetation covers, bare soil, water surface, various urban areas, etc. Land cover and its changes are very important and influential on the Earth and life of living organisms, especially human beings. Land cover change monitoring is important for protecting the ecosystem, forests, farmland, open spac...
متن کاملFeature Extraction of Visual Evoked Potentials Using Wavelet Transform and Singular Value Decomposition
Introduction: Brain visual evoked potential (VEP) signals are commonly known to be accompanied by high levels of background noise typically from the spontaneous background brain activity of electroencephalography (EEG) signals. Material and Methods: A model based on dyadic filter bank, discrete wavelet transform (DWT), and singular value decomposition (SVD) was developed to analyze the raw data...
متن کاملAuthor gender identification from text using Bayesian Random Forest
Nowadays high usage of users from virtual environments and their connection via social networks like Facebook, Instagram, and Twitter shows the necessity of finding out shared subjects in this environment more than before. There are several applications that benefit from reliable methods for inferring age and gender of users in social media. Such applications exist across a wide area of fields,...
متن کاملDetermining Data Relevance Using Semantic Types and Graphical Interpretation Cues
The increasing volume of data generated and the shortage of professionals trained to extract value from it, raises a question of how to automate data analysis processes. This work investigates how to increase the automation in the data interpretation process by proposing a relevance classification heuristic model, which can be used to express which views over the data are potentially meaningful...
متن کاملReal Time Driver’s Drowsiness Detection by Processing the EEG Signals Stimulated with External Flickering Light
The objective of this study is development of driver’s sleepiness using Visually Evoked Potentials (VEP). VEP computed from EEG signals from the visual cortex. We use the Steady State VEPs (SSVEPs) that are one of the most important EEG signals used in human computer interface systems. SSVEP is a response to visual stimuli presented. We present a classification method to discriminate between...
متن کامل