Hybrid Deep Learning Framework for Road Surface Classification: Integrating Autoencoder-Based Denoising and CNN-Based Classification

This study uses a hybrid deep learning technique to classify asphalt, pavement, and unpaved roads. In real-world circumstances, image data noise can damage image categorization algorithms. This issue can be addressed by a deep neural network (DNN)-based classification system that uses advanced denoi...

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Veröffentlicht in:	2025 International Conference on Intelligent Control, Computing and Communications (IC3) S. 487 - 492
Hauptverfasser:	Kumar, Ajay, Tiwari, Raj Gaurang, Trivedi, Naresh Kumar
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 13.02.2025
Schlagworte:	Accuracy Autoencoders Classification algorithms Computer architecture Convolutional Denoising Autoencoder Convolutional neural networks Deep learning Deep Neural Networks Denoising Autoencoder Hybrid Deep Learning Image Reconstruction Noise Noise measurement Noise reduction Noise Reduction Techniques Noisy Image Classification Road Surface Classification Roads
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