A Hybrid Object Recognition Architecture
نویسندگان
چکیده
We present an architecture for 3D-object recognition based on the integration of neural and semantic networks. The architecture consists of mainly two components. A neural object recognition system generates object hypotheses, which are veriied or rejected by a semantic network. Thus the advantages of both paradigms are combined: in the low level eld adaptivity and the ability to learn from examples is realized by a neural network, whereas the high level analysis is performed by representing structured knowledge in a semantic network.
منابع مشابه
Urban Vegetation Recognition Based on the Decision Level Fusion of Hyperspectral and Lidar Data
Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers. The combination of these data improves the obje...
متن کاملA Distributed Control Architecture for Autonomous Operation of a Hybrid AC/DC Microgrid System
Hybrid AC/DC microgrids facilitate the procedure of DC power connection into the conventional AC power system by developing the distributed generations (DGs) technologies. The conversion processes between AC and DC electrical powers are more convenient by hybrid systems. In this paper, an energy management system (EMS) for a hybrid microgrid network is proposed due to the optimal utilization of...
متن کاملRecognition of Cognition Issue in Islamic Architecture Creation
Recognizing the link between “Cognition" and "Architectural Creation” indicates that there is a relation between subject and object. Correct understanding of this relationship helps artistic creativity, especially in the architecture, to take steps towards proving truth that have caused works to be continued over the past times. Knowledge and cognitions in architecture are categories that today...
متن کاملRGB-D Training for Convolutional Neural Network with Final Fuzzy Layer for Depth Weighting
This paper presents training of novel hybrid network based on three deep convolutional neural network architectures applied to object recognition, based on the depth information supplied for a RGBD camera. For this case, the depth information allows to set the dataset of training images of each network, its architecture and its characteristics, generating a dynamic recognition application by va...
متن کاملDemonstration of phenomenological approach’s proportion, for vernacular ARCHITECTURE recognition (Case Study: Vernacular Housing in Manoojan Region of Kerman Province)
Although the vernacular architecture is formed in harmony with the "lived experience" of the natives, looking at the studies of vernacular architecture, we see that in the researches done, researchers have paid more attention to the role of factors such as social, cultural, religious, economic, physical, climatic, construction technology and materials; And so far, researches done in the field o...
متن کامل