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Found 7 papers, 1 papers with code
Sidewalk Measurements from Satellite Images: Preliminary Findings
Large-scale analysis of pedestrian infrastructures, particularly sidewalks, is critical to human-centric urban planning and design.
Unraveling the graph structure of tabular data through Bayesian and spectral analysis
With this graph of relationships, we show that the inference of the hierarchical modular structure obtained by the Nested Stochastic Block Model (nSBM) as well as the study of the spectral space of the magnetic Laplacian can help us identify the classes of features and unravel non-trivial relationships.
Revisiting Agglomerative Clustering
An important issue in clustering concerns the avoidance of false positives while searching for clusters.
Quantifying the presence of graffiti in urban environments
Graffiti is a common phenomenon in urban scenarios.
Single Image Deraining: A Comprehensive Benchmark Analysis
We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy images. This dataset highlights diverse data sources and image contents, and is divided into three subsets (rain streak, rain drop, rain and mist), each serving different training or evaluation purposes.
A new approach for pedestrian density estimation using moving sensors and computer vision
However, such methods do not scale to the size of a city and a new approach to fill this gap is here proposed.
Identificação automática de pichação a partir de imagens urbanas
Graffiti tagging is a common issue in great cities an local authorities are on the move to combat it.
