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Found 6 papers, 0 papers with code
Multistep traffic speed prediction: A deep learning based approach using latent space mapping considering spatio-temporal dependencies
In recent years, a number of different methods for traffic prediction have been proposed which have proved their effectiveness in terms of accuracy.
L2BGAN: An image enhancement model for image quality improvement and image analysis tasks without paired supervision
The paper presents an image enhancement model, L2BGAN, to translate low light images to bright images without a paired supervision.
Convolutional Neural Network-Bagged Decision Tree: A hybrid approach to reduce electric vehicle's driver's range anxiety by estimating energy consumption in real-time
To overcome range anxiety problem of Electric Vehicles (EVs), an accurate real-time energy consumption estimation is necessary, which can be used to provide the EV's driver with information about the remaining range in real-time.
Estimation of energy consumption of electric vehicles using Deep Convolutional Neural Network to reduce driver's range anxiety
The goal of this work is to reduce driver's range anxiety by estimating the real-time energy consumption of electric vehicles using deep convolutional neural network.
A Convolutional Feature Map based Deep Network targeted towards Traffic Detection and Classification
This research mainly emphasizes on traffic detection thus essentially involving object detection and classification.
A scene perception system for visually impaired based on object detection and classification using multi-modal DCNN
This paper represents a cost-effective scene perception system aimed towards visually impaired individual.
