Search results for "Hine"
showing 10 items of 5088 documents
Design and Calibration of a Specialized Polydioptric Camera Rig
2017
International audience; It has been observed in the nature that all creatures have evolved highly exclusive sensory organs depending on their habitat and the form of resources availability for their survival. In this project, a novel omnidirectional camera rig, inspired from natural vision sensors, is proposed. It is exclusively designed to operate for highly specified tasks in the field of mobile robotics. Navigation problems on uneven terrains and detection of the moving objects while the robot is itself in motion are the core problems that omnidirectional systems tackle. The proposed omnidirectional system is a compact and a rigid vision system with dioptric cameras that provide a 360° f…
MFNet: Multi-feature convolutional neural network for high-density crowd counting
2020
The crowd counting task involves the issue of security, so now more and more people are concerned about it. At present, the most difficult problem of population counting consists in: how to make the model distinguish human head features more finely in the densely populated area, such as head overlap and how to find a small-scale local head feature in an image with a wide range of population density. Facing these challenges, we propose a network for multiple feature convolutional neural network, which is called MFNet. It aims to get high-quality density maps in the high-density crowd scene, and at the same time to perform the task of the count and estimation of the crowd. In terms of crowd c…
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
Me, My Bot and His Other (Robot) Woman? Keeping Your Robot Satisfied in the Age of Artificial Emotion
2018
With a backdrop of action and science fiction movie horrors of the dystopian relationship between humans and robots, surprisingly to date-with the exception of ethical discussions-the relationship aspect of humans and sex robots has seemed relatively unproblematic. The attraction to sex robots perhaps is the promise of unproblematic affectionate and sexual interactions, without the need to consider the other&rsquo
An Artificial Bee Colony Approach for Classification of Remote Sensing Imagery
2018
This paper presents a novel Artificial Bee Colony (ABC) approach for supervised classification of remote sensing images. One proposes to apply an ABC algorithm to optimize the coefficients of the set of polynomial discriminant functions. We have experimented the proposed ABC-based classifier algorithm for a Landsat 7 ETM+ image database, evaluating the influence of the ABC model parameters on the classifier performances. Such ABC model parameters are: numbers of employed/onlooker/scout bees, number of epochs, and polynomial degree. One has compared the best ABC classifier Overall Accuracy (OA) with the performances obtained using a set of benchmark classifiers (NN, NP, RBF, and SVM). The re…
PolyACO+: a multi-level polygon-based ant colony optimisation classifier
2017
Ant Colony Optimisation for classification has mostly been limited to rule based approaches where artificial ants walk on datasets in order to extract rules from the trends in the data, and hybrid approaches which attempt to boost the performance of existing classifiers through guided feature reductions or parameter optimisations. A recent notable example that is distinct from the mainstream approaches is PolyACO, which is a proof of concept polygon-based classifier that resorts to ant colony optimisation as a technique to create multi-edged polygons as class separators. Despite possessing some promise, PolyACO has some significant limitations, most notably, the fact of supporting classific…
A flexible robotic cell for in-process inspection of multi-pass welds
2020
Welds are currently only inspected after all the passes are complete and after allowing sufficient time for any hydrogen cracking to develop, typically over several days. Any defects introduced between passes are therefore unreported until fully buried, greatly complicating rework and also delaying early corrections to the weld process parameters. In-process inspection can provide early intervention but involves many challenges, including operation at high temperatures with significant gradients affecting acoustic velocities and, hence, beam directions. Reflections from the incomplete parts of the weld would also be flagged as lack-of-fusion defects, requiring the region of interest (ROI) t…
A Novel Border Identification Algorithm Based on an “Anti-Bayesian” Paradigm
2013
Published version of a chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_23 Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the border of the classes, and have sufficient information to perform a meaningful classification. However, one can see that the true border patterns (“near” border) are not able to perform the task independently as they are not able to always distinguish the testing samples. Thus, researchers have worked on thi…
Variable neighborhood descent for the incremental graph drawing
2017
Abstract Graphs are used to represent reality in several areas of knowledge. Drawings of graphs have many applications, from project scheduling to software diagrams. The main quality desired for drawings of graphs is readability, and crossing reduction is a fundamental aesthetic criterion for a good representation of a graph. In this paper we target the edge crossing reduction in the context of incremental graph drawing, in which we want to preserve the layout of a graph over successive drawings. We propose a hybrid method based on the GRASP (Greedy Randomized Adaptive Search Procedure) and VND (Variable Neighborhood Descent) methodologies and compare it with previous methods via simulation.
Evaluation of Coded Excitations for Autonomous Airborne Ultrasonic Inspection
2019
Unmanned Aerial Vehicles (UAVs) are receiving increasing attention for use in Non-Destructive Testing due to their ability to access areas where manual inspection is not practical. Contact-based UAV ultrasonic inspections grant the opportunity to remotely monitor the structural health of an industrial asset with enhanced internal integrity information. Ultrasonic inspection is a Non-Destructive Testing (NDT) method conventionally used in corrosion mapping. Surface contacting ultrasonic transducers provide enhanced structural integrity information. However, due to near-surface aerodynamic effects, angular sensitivity of the ultrasound probe and alignment error during autonomous inspections, …