Search results for "Feature recognition"
showing 3 items of 3 documents
Intelligent agents for feature modelling in computer aided design
2017
Abstract CAD modelling can be referred to as the process of generating an integrated multiple view model as a representation of multiple views of engineering design. In many situations, a change in the model of one view may conflict with the models of other views. In such situations, the model of some views needs to be adapted in order to make all models consistent. Thus, CAD models should be capable of adapting themselves to new situations. Recently, agent based technologies have been considered in order to increase both knowledge level and intelligence of real and virtual objects. The contribution of this paper consists in introducing the intelligent agents in intelligent CAD modelling. T…
The Anatomy of an Optical Biopsy Semantic Retrieval System
2012
A case-based computer-aided diagnosis system assists physicians and other medical personnel in the interpretation of optical biopsies obtained through confocal laser endomicroscopy. Extraction in CLE images shows promising results on inferring semantic metadata from low-level features. In order to effectively ensure the interoperability with potential third-party applications, the system provides an interface compliant with the recent standards ISO/IEC 15938-12:2008 (MPEG Query Format) and ISO/IEC 24800 (JPEG Search).
Application of EαNets to Feature Recognition of Articulation Manner in Knowledge-Based Automatic Speech Recognition
2006
Speech recognition has become common in many application domains. Incorporating acoustic-phonetic knowledge into Automatic Speech Recognition (ASR) systems design has been proven a viable approach to rise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as detectors for manner of articulation attributes starting from representations of speech signal frames. In this paper, a set of six detectors for the above mentioned attributes is designed based on the E-αNet model of neural networks. This model was chosen for its capability to learn hidden acti…