Search results for "cognition."
showing 10 items of 7004 documents
Abnormal Textures Identification Based on Digital Hilbert Optics Methods: Fundamental Transforms and Models
2017
The article presents the abnormal textures identification technology based on structural and statistical models of amplitude-phase images (APIm) – multidimensional data arrays (semantic models) and statistical correlation analysis methods using the generalized discrete Hilbert transforms (DHT) – 2D Hilbert (Foucault) isotropic (HTI), anisotropic (HTA) and total transforms – AP-analysis (APA) to calculate the APIm. The identified fragments of textures are obtained as examples of experimental observation of real mammograms contains areas of pathological tissues. The DHT based information technology as conceptual chart description is discussed and illustrated with DHO domain images. As additio…
Tracking Moving Objects With a Catadioptric Sensor Using Particle Filter
2011
International audience; Visual tracking in video sequences is a widely developed topic in computer vision applications. However, the emergence of panoramic vision using catadioptric sensors has created the need for new approaches in order to track an object in this type of images. Indeed the non-linear resolution and the geometric distortions due to the insertion of the mirror, make tracking in catadioptric images a very challenging task. This paper describes particle filter for tracking moving object over time using a catadioptric sensor. In this work different problems due to the specificities of the catadioptric systems such as geometry are considered. The obtained results demonstrate an…
An insight into the electrical energy demand of friction stir welding processes: the role of process parameters, material and machine tool architectu…
2018
The manufacturing sector accounts for a high share of global electrical energy consumption and CO 2 emissions, and therefore, the environmental impact of production processes is being more and more investigated. An analysis of power and energy consumption in friction stir welding processes can contribute to the characterization of the process from a new point of view and also provide useful information about the environmental impact of the process. An in-depth analysis of electrical energy demand of friction stir welding is here proposed. Different machine tool architectures, including an industrial dedicated machine, have been used to weld aluminum and steel sheets under different process …
Types of Mimetics for the Design of Intelligent Technologies
2019
Mimetic design means using a source in the natural or artificial worlds as an inspiration for technological solutions. It is based around the abstraction of the relevant operating principles in a source domain. This means that one must be able to identify the correct level of analysis and extract the relevant patterns. How this should be done is based on the type of source. From a mimetic perspective, if the design goal is intelligent technology, an obvious source of inspiration is human information processing, which we have called cognitive mimetics. This article offers some conceptual clarification on the nature of cognitive mimetics by contrasting it with biomimetics in the context of in…
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…
Overview of the Development of Hydraulic Above Knee Prosthesis
2017
This paper presents research and development of hydraulically powered above-knee prosthesis (HAKP) and novel prosthetic foot, in order to enable transfemoral (TF) amputees perform stair ascent and other daily activities in as much as possible natural manner. Functions that need exertion of large forces and moments during locomotion such as walking up stairs and slopes cannot be naturally accomplished by commercially available microprocessor-controlled above-knee (AK) prostheses. Also, such prosthetic devices are expensive and unaffordable for major part of amputee population, so mostly used commercial prostheses are energetically passive devices. Deficiency of passive prosthetic devices is …
New delay-dependent stability of Markovian jump neutral stochastic systems with general unknown transition rates
2015
This paper investigates the delay-dependent stability problem for neutral Markovian jump systems with generally unknown transition rates GUTRs. In this neutral GUTR model, each transition rate is completely unknown or only its estimate value is known. Based on the study of expectations of the stochastic cross-terms containing the integral, a new stability criterion is derived in terms of linear matrix inequalities. In the mathematical derivation process, bounding stochastic cross-terms, model transformation and free-weighting matrix are not employed for less conservatism. Finally, an example is provided to demonstrate the effectiveness of the proposed results.
Dissipativity-Based Small-Gain Theorems for Stochastic Network Systems
2016
In this paper, some small-gain theorems are proposed for stochastic network systems which describe large-scale systems with interconnections, uncertainties and random disturbances. By the aid of conditional dissipativity and showing times of stochastic interval, small-gain conditions proposed for the deterministic case are extended to the stochastic case. When some design parameters are tunable in practice, we invaginate a simpler method to verify small-gain condition by selecting one subsystem as a monitor. Compared with the existing results, the existence-and-uniqueness of solution and ultimate uniform boundedness of input are removed from requirements of input-to-state stability and smal…
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…