Search results for "cognitive neuroscience"
showing 10 items of 1135 documents
A meta-cognitive architecture for planning in uncertain environments
2013
Abstract The behavior of an artificial agent performing in a natural environment is influenced by many different pressures and needs coming from both external world and internal factors, which sometimes drive the agent to reach conflicting goals. At the same time, the interaction between an artificial agent and the environment is deeply affected by uncertainty due to the imprecision in the description of the world, and the unpredictability of the effects of the agent’s actions. Such an agent needs meta-cognition in terms of both self-awareness and control. Self-awareness is related to the internal conditions that may possibly influence the completion of the task, while control is oriented t…
Entropy-based Localization of Textured Regions
2011
Appearance description is a relevant field in computer vision that enables object recognition in domains as re-identification, retrieval and classification. Important cues to describe appearance are colors and textures. However, in real cases, texture detection is challenging due to occlusions and to deformations of the clothing while person's pose changes. Moreover, in some cases, the processed images have a low resolution and methods at the state of the art for texture analysis are not appropriate. In this paper, we deal with the problem of localizing real textures for clothing description purposes, such as stripes and/or complex patterns. Our method uses the entropy of primitive distribu…
QUALI FENOMENI PER L’ESTETICA EMPIRICA?
2020
Empirical Aesthetics profits from the research in Cognitive Neurosciences and the target article collects multiple evidence on the neurobiological basis of art and aesthetic experience in order to submit that psychological models give a new definition of the field of Psychology of Arts, if they integrate this empirical evidence with the perceptual, emotional and cognitive capacities, which are assumed to give rise to art and aesthetic experience. The opinion article raises questions about the variety of phenomena in the field, the common methodology to experimental research on cognition and aesthetics, the manifold perceptual attributes which support art and aesthetic cognition, the potenti…
Towards a unified process model for graphemic buffer disorder and deep dysgraphia
2006
Models based on the competitive queuing (CQ) approach can explain many of the effects on dysgraphic patients’ spelling attributed to disruption of the “graphemic output buffer”. Situating such a model in the wider spelling system, however, raises the question of what happens when input to the buffer (e.g., from a semantic system) is degraded while the buffer remains intact. We present a preliminary exploration of predictions following from the CQ approach. We show that the CQ account of the graphemic buffer predicts and explains the finding that deep dysgraphic patients generally show features of graphemic buffer disorder, as disrupted input from a damaged semantic system has an inevitable …
Signal reconstruction, modeling and simulation of a vehicle full-scale crash test based on Morlet wavelets
2012
Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this paper a novel wavelet-based approach is introduced to reproduce acceleration pulse of a vehicle involved in a crash event. The acceleration of a colliding vehicle is measured in its center of gravity-this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of…
Views selection for SIFT based object modeling and recognition
2016
In this paper we focus on automatically learning object models in the framework of keypoint based object recognition. The proposed method uses a collection of views of the objects to build the model. For each object the collection is composed of N×M views obtained rotating the object around its vertical and horizontal axis. As keypoint based object recognition using a complete set of views is computationally expensive, we focused on the definition of a selection method that creates, for each object, a subset of the initial views that visually summarize the characteristics of the object and should be suited for recognition. We select the views by determining maxima and minima of a function, …
PORE Algorithm for Object Recognition in Photo Layers based on Parametric Characteristics of the Object Edges
2016
PORE stands for Photo-Object Recognition based on the Edges. Coincidentally, PORE means to examine something carefully and with due attention, so "we pore over the object layers in search for information about their characteristics with the aim at improving image recognition process". Therefore, this study presents a novel approach to object recognition based on the pattern by using photo layers and by defining the objects' specific characteristics. We select and introduce the parameters which determine a higher efficiency of image retrieval of the image objects. In this paper, we describe how the same photos are recognized in a process of classical retrieval compared to our model by analyz…
Biopoetica
2022
Siri Hustvedt, una scrittrice che ha saputo sempre coniugare l’analisi del proprio bíos – della pro- pria “fragilità” psichica e fisica – con la teoria della narrativa, con particolare attenzione per le articolazioni della “mente narrativa”: le emozioni, l’immaginazione, la memoria. Siri Hustvedt nelle sue opere alterna profonde analisi psicologiche di carattere narrativo, in particolare autobiografico, e riflessioni saggistiche in cui centrale è il confronto con la più recente e agguerrita letteratura neuroscientifica. Siri Hustvedt, a writer who has always known how to combine the analysis of her own bios - of her psychic and physical "fragility" - with the theory of fiction, with particu…
3D objects descriptors methods: Overview and trends
2017
International audience; Object recognition or object's category recognition under varying conditions is one of the most astonishing capabilities of human visual system. The scientists in computer vision have been trying for decades to reproduce this ability by implementing algorithms and providing computers with appropriate tools. Hence, several intelligent systems have been proposed. To act in this field, numerous approaches have been proposed. In this paper we present an overview of the current trend in 3D objects recognition and describe some representative state of the art methods, highlighting their limits and complexity.
Automatic recognition of rapid eye movement (REM) sleep by artificial neural networks.
1995
Artificial neural networks are well known for their good performance in pattern recognition. Their suitability for detecting REM sleep periods on the basis of preprocessed EEG data in humans under clinical conditions was tested and their performance compared with the manual evaluation. A single channel of the EEG signal was analysed in time periods of 20 s and preprocessed into a vector of six real numbers, which served as input to the network. EOG and EMG information was ignored. Backpropagation was used as a learning rule for the network, which consisted of 12 neurons and 39 synapses. Training datasets were put together from the input vectors and the corresponding sleep stages were scored…