Search results for "Object Recognition"
showing 10 items of 67 documents
A modeling study suggesting how a reduction in the context-dependent input on CA1 pyramidal neurons could generate schizophrenic behavior.
2011
The neural mechanisms underlying schizophrenic behavior are unknown and very difficult to investigate experimentally, although a few experimental and modeling studies suggested possible causes for some of the typical psychotic symptoms related to this disease. The brain region most involved in these processes seems to be the hippocampus, because of its critical role in establishing memories for objects or events in the context in which they occur. In particular, a hypofunction of the N-methyl-D-aspartate (NMDA) component of the synaptic input on the distal dendrites of CA1 pyramidal neurons has been suggested to play an important role for the emergence of schizophrenic behavior. Modeling st…
Mitochondrial cannabinoid receptors gate corticosterone impact on novel object recognition
2023
: Corticosteroid-mediated stress responses require the activation of complex brain circuits involving mitochondrial activity, but the underlying cellular and molecular mechanisms are scantly known. The endocannabinoid system is implicated in stress coping, and it can directly regulate brain mitochondrial functions via type 1 cannabinoid (CB1) receptors associated with mitochondrial membranes (mtCB1). In this study, we show that the impairing effect of corticosterone in the novel object recognition (NOR) task in mice requires mtCB1 receptors and the regulation of mitochondrial calcium levels in neurons. Different brain circuits are modulated by this mechanism to mediate the impact of cortico…
Hybrid Methods for Robust Irradiance Analysis and 3-D Shape Reconstruction from Images
1994
The analysis of the differential structure of images is an interesting task in machine vision, among other reasons because it can provide relevant featural representation of images, suited for higher level information processing task like geometry reconstruction and object recognition. The importance of invariants of the field of isophotae on lambertian surfaces in shape perception by means of chiaroscuro is discussed in (Koenderink and Van Doom, 1980). In their approach to shape from shading, (Breton et al, 1992) represent the shading of the image by means of its shading flow field, i.e. by the first order differential structure of the image expressed as the isoluminance direction and grad…
Topographic Independent Component Analysis reveals random scrambling of orientation in visual space
2017
Neurons at primary visual cortex (V1) in humans and other species are edge filters organized in orientation maps. In these maps, neurons with similar orientation preference are clustered together in iso-orientation domains. These maps have two fundamental properties: (1) retinotopy, i.e. correspondence between displacements at the image space and displacements at the cortical surface, and (2) a trade-off between good coverage of the visual field with all orientations and continuity of iso-orientation domains in the cortical space. There is an active debate on the origin of these locally continuous maps. While most of the existing descriptions take purely geometric/mechanistic approaches whi…
Classification based on Iterative Object Symmetry Transform
2004
The paper shows an application of a new operator named the iterated object transform (IOT) for cell classification. The IOT has the ability to grasp the internal structure of a digital object and this feature can be usefully applied to discriminate structured images. This is the case of cells representing chondrocytes in bone tissue, giarda protozoan, and myeloid leukaemia. A tree classifier allows us to discriminate the three classes with a good accuracy.
A Neural Architecture for Segmentation and Modelling of Range Data
2003
A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural stages: a SOM is used to perform data segmentation, and, for each segment, a multi-layer feed-forward network performs model estimation. The topology preserving nature of the SOM algorithm makes this architecture suited to cluster data with respect to sudden curvature variations. The second stage is designed to model and compute the inside-outside function of an undeformed superquadric in whatever attitude, starting form the (x, y, z) data triples. The network has been trained using backpropagation, and the we…
LeSSS: Learned Shared Semantic Spaces for Relating Multi-Modal Representations of 3D Shapes
2015
In this paper, we propose a new method for structuring multi-modal representations of shapes according to semantic relations. We learn a metric that links semantically similar objects represented in different modalities. First, 3D-shapes are associated with textual labels by learning how textual attributes are related to the observed geometry. Correlations between similar labels are captured by simultaneously embedding labels and shape descriptors into a common latent space in which an inner product corresponds to similarity. The mapping is learned robustly by optimizing a rank-based loss function under a sparseness prior for the spectrum of the matrix of all classifiers. Second, we extend …
Reward-related limbic memory and stimulation of the cannabinoid system: An upgrade in value attribution?
2018
While a lot is known about the mechanisms promoting aversive learning, the impact of rewarding factors on memory has received comparatively less attention. This research investigates reward-related explicit memory in male rats, by taking advantage of the emotional-object recognition test. This is based on the prior association, during conditioned learning, between a rewarding experience (the encounter with a receptive female rat) and an object; afterwards rat discrimination and recognition of the â emotional objectâ is recorded in the presence of a novel object, as a measure of positive limbic memory formation. Since endocannabinoids are critical for processing reward and motivation, the co…
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…
Multi-agent control architecture for RFID cyberphysical robotic systems initial validation of tagged objects detection and identification using Playe…
2016
International audience; The objective of this paper is to describe and validate a multi-agent architecture proposed to control RFID Cyber-Physical Robotic Systems. This environment may contain human operators, robots (mobiles, manipulators, mobile manipulators, etc.), places (workrooms, walls, etc.) and other objects (tables, chairs, etc.). The proposed control architecture is composed of two types of agents dispatched on two levels. We find at the Organization level a Supervisory agent to allow operators to configure, manage and interact with the overall control system. At the Control level, we distinguish the Robots agents, to each robot (mobiles, manipulators or mobile manipulators) is a…