Early Classifying Multimodal Sequences

05/02/2023
by   Alexander Cao, et al.
0

Often pieces of information are received sequentially over time. When did one collect enough such pieces to classify? Trading wait time for decision certainty leads to early classification problems that have recently gained attention as a means of adapting classification to more dynamic environments. However, so far results have been limited to unimodal sequences. In this pilot study, we expand into early classifying multimodal sequences by combining existing methods. We show our new method yields experimental AUC advantages of up to 8.7

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/07/2023

A Policy for Early Sequence Classification

Sequences are often not received in their entirety at once, but instead,...
research
04/04/2017

From Modal to Multimodal Ambiguities: a Classification Approach

This paper deals with classifying ambiguities for Multimodal Languages. ...
research
12/18/2020

ReINTEL Challenge 2020: A Multimodal Ensemble Model for Detecting Unreliable Information on Vietnamese SNS

In this paper, we present our methods for unrealiable information identi...
research
06/26/2023

Multivariate Time Series Early Classification Across Channel and Time Dimensions

Nowadays, the deployment of deep learning models on edge devices for add...
research
04/06/2023

Classifying sequences by combining context-free grammars and OWL ontologies

This paper describes a pattern to formalise context-free grammars in OWL...
research
04/30/2019

Multimodal Classification of Urban Micro-Events

In this paper we seek methods to effectively detect urban micro-events. ...
research
04/25/2019

Sequential Decision Fusion for Environmental Classification in Assistive Walking

Powered prostheses are effective for helping amputees walk on level grou...

Please sign up or login with your details

Forgot password? Click here to reset