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Found 6 papers, 5 papers with code
Combining geolocation and height estimation of objects from street level imagery
We propose a pipeline for combined multi-class object geolocation and height estimation from street level RGB imagery, which is considered as a single available input data modality.
Tensor Reordering for CNN Compression
We show how parameter redundancy in Convolutional Neural Network (CNN) filters can be effectively reduced by pruning in spectral domain.
Harmonic Convolutional Networks based on Discrete Cosine Transform
Convolutional neural networks (CNNs) learn filters in order to capture local correlation patterns in feature space.
Ranked #452 on
Image Classification
on ImageNet
Harmonic Networks with Limited Training Samples
In the context of reverting to preset filters, we propose here a computationally efficient harmonic block that uses Discrete Cosine Transform (DCT) filters in CNNs.
Ranked #34 on
Image Classification
on STL-10
Harmonic Networks: Integrating Spectral Information into CNNs
Convolutional neural networks (CNNs) learn filters in order to capture local correlation patterns in feature space.
Automatic Discovery and Geotagging of Objects from Street View Imagery
Many applications such as autonomous navigation, urban planning and asset monitoring, rely on the availability of accurate information about objects and their geolocations.
