Enhancing Ability of Autonomous Vehicles to Detect Objects in Diverse Environments and Weather Conditions

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Dr. Shannon Abolmaali
Erick Jones

Abstract

The ability of autonomous vehicles to
detect objects and obstacles in various
weather conditions, such as rain and fog
has become a challenge. The weather
conditions make it even harder to


accurately and precisely detect objects.
Convolutional neural networks and CNN
models work as multiple deep learning
models utilizing data to increase the
model's performance. The technique for
data augmentation is helpful for limited
training for the applications. The framework
is then applied to the algorithm in two
layers, single model and multi-model

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