The Importance of Loss Functions for Increasing the Generalization Abilities of a Deep Learning-Based Next Frame Prediction Model for Traffic Scenes

The Importance of Loss Functions for Increasing the Generalization Abilities of a Deep Learning-Based Next Frame Prediction Model for Traffic Scenes

This paper analyzes in detail how different loss functions influence the generalization abilities of a deep learning-based next frame prediction model for traffic scenes. Our prediction model is a convolutional long-short term memory (ConvLSTM) network that generates the pixel values of the next fra...

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Bibliographic Details
Main Authors: Sandra Aigner, Marco Körner
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Machine Learning and Knowledge Extraction
Subjects:
traffic scene prediction
video prediction
generalization
convolutional LSTMs
recurrent neural networks
machine learning
Online Access:https://www.mdpi.com/2504-4990/2/2/6

Internet

https://www.mdpi.com/2504-4990/2/2/6

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