Search results for "Image"

Tractional Motion Machines: Tangent-Managing Planar Mechanisms as Analog Computers and Educational Artifacts

2012

Concrete and virtual machines play a central role in the both Unconventional Computing (machines as computers) and in Math Education (influence of artifacts on reaching/producing abstract thought). Here we will examine some fallouts in these fields for the Tractional Motion Machines, planar mechanisms based on some devices used to plot the solutions of differential equations by the management of the tangent since the late 17th century.

Highlights of Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection

2014

Least-squares community extraction in feature-rich networks using similarity data

2021

We explore a doubly-greedy approach to the issue of community detection in feature-rich networks. According to this approach, both the network and feature data are straightforwardly recovered from the underlying unknown non-overlapping communities, supplied with a center in the feature space and intensity weight(s) over the network each. Our least-squares additive criterion allows us to search for communities one-by-one and to find each community by adding entities one by one. A focus of this paper is that the feature-space data part is converted into a similarity matrix format. The similarity/link values can be used in either of two modes: (a) as measured in the same scale so that one may …

Experiencing with electronic image stabilization and PRNU through scene content image registration

2021

Abstract This paper explores content-based image registration as a means of dealing with and understanding better Electronic Image Stabilization (EIS) in the context of Photo Response Non-Uniformity (PRNU) alignment. A novel and robust solution to extrapolate the transformation relating the different image output formats for a given device model is proposed. This general approach can be adapted to specifically extract the scale factor (and, when appropriate, the translation) so as to align native resolution images to video frames, with or without EIS on, and proceed to compare PRNU patterns. Comparative evaluations show that the proposed approach outperforms those based on brute-force and p…

Smart Mobility Trends: Open Data and Other Tools

2018

The Strategic Implementation Plan for speeding up the transformation of European Cities into "Smart cities" establishes 6 Actions Clusters and 11 Priority Areas. Some of them are directly related to the transport and sustainable urban mobility. The main goal is the application of new technologies to minimize the loss of time and energy, and to improve the satisfaction of citizens. The use and reuse of information as open data, already collected from the Public Administration and private entities is a source of possibilities adding extra value. Technologies such as Bluetooth sensors, Open Data platforms etc., become essential elements to achieve this goal. This paper highlights the opportuni…

Entropy-Based Classifier Enhancement to Handle Imbalanced Class Problem

2017

The paper presents a possible enhancement of entropy-based classifiers to handle problems, caused by the class imbalance in the original dataset. The proposed method was tested on synthetic data in order to analyse its robustness in the controlled environment with different class proportions. As also the proposed method was tested on the real medical data with imbalanced classes and compared to the original classification algorithm results. The medical field was chosen for testing due to frequent situations with uneven class ratios.

Efficient Multi-scale Patch-Based Segmentation

2015

The objective of this paper is to devise an efficient and accurate patch-based method for image segmentation. The method presented in this paper builds on the work of Wu et al. [14] with the introduction of a compact multi-scale feature representation and heuristics to speed up the process. A smaller patch representation along with hierarchical pruning allowed the inclusion of more prior knowledge, resulting in a more accurate segmentation. We also propose an intuitive way of optimizing the search strategy to find similar voxel, making the method computationally efficient. An additional approach at improving the speed was explored with the integration of our method with Optimised PatchMatch…

Area-Based Depth Estimation for Monochromatic Feature-Sparse Orthographic Capture

2018

With the rapid development of light field technology, depth estimation has been highlighted as one of the critical problems in the field, and a number of approaches have been proposed to extract the depth of the scene. However, depth estimation by stereo matching becomes difficult and unreliable when the captured images lack both color and feature information. In this paper, we propose a scheme that extracts robust depth from monochromatic, feature-sparse scenes recorded in orthographic sub-aperture images. Unlike approaches which rely on the rich color and texture information across the sub-aperture views, our approach is based on depth from focus techniques. First, we superimpose shifted …

POLARIZATION-BASED CAR DETECTION

2018

International audience; Road scene understanding is a vital task for driving assistance systems. Robust vehicle detection is a precondition for diverse applications particularly for obstacle avoidance and secure navigation. Color images provide limited information about the physical properties of the object. This results in unstable vehicle detection caused mainly from road scene complexity (strong reflexions, noises and radiometric distortions). Instead, polarimetric images, characteristic of the light wave, can robustly describe important physical properties of the object (e.g., the surface geometric structure, material and roughness etc). This modality gives rich physical informations wh…

Estimation of brain connectivity through Artificial Neural Networks

2019

Among different methods available for estimating brain connectivity from electroencephalographic signals (EEG), those based on MVAR models have proved to be flexible and accurate. They rely on the solution of linear equations that can be pursued through artificial neural networks (ANNs) used as MVAR model. However, when few data samples are available, there is a lack of accuracy in estimating MVAR parameters due to the collinearity between regressors. Moreover, the assessment procedure is also affected by the lack of data points. The mathematical solution to these problems is represented by penalized regression methods based on l 1 norm, that can reduce collinearity by means of variable sel…