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End To End Autonomous Driving Behavior Prediction Based On Deep Convolution Neural Network by fahadm2718 is a document available to read on EtoBox.

This document presents a study on end-to-end autonomous driving behavior prediction using a deep convolutional neural network, specifically an ECA-ResNet50 model that integrates an effective channel attention mechanism. The model aims to improve prediction accuracy by effectively extracting spatial features from RGB images and mapping them to steering angle outputs. Experimental results indicate that this approach outperforms traditional CNN models in driving behavior prediction accuracy.

Author

fahadm2718

Language

EN