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Full-Text Articles in Physical Sciences and Mathematics
Neuro-Fuzzy Models For Classification And Rule Generation., Sushmita Mitra Dr.
Neuro-Fuzzy Models For Classification And Rule Generation., Sushmita Mitra Dr.
Doctoral Theses
Machine recognition [1, 2] of patterns can be viewed as a two-fold task, consisting of learning the invariant and common properties of a set of samples characterizing a class, and of deciding a new sample as a possible member of the class by noting that it has properties common to those of the set of samples. In other words, pattern recognition by computers can be described as a transformation from the measurenment space M to the feature space F and finally to the decision space D (1), i.e., M ⟶F⟶D.Here, the mapping 6 : F⟶D is the decision function and …
Connectionist Models For Certain Tasks Related To Object Recognition., Jayanta Basak Dr.
Connectionist Models For Certain Tasks Related To Object Recognition., Jayanta Basak Dr.
Doctoral Theses
Recognition of objects in an image, according to Suetens et al. [1), relers to the task of finding and labeling parts of a two-dimensional image of a scene that correspond to the real objects in the scene. Object recognition is necessary in a variety of domains like robot navigation, aerial imagery analysis, industrial inspection and so on. Normally, different strategies for object recognition (1-(5] involve establishing some model for each object, i.e., some general description of each object, and then labeling different parts of the scene according to the knowledge about the models.Object models can have two-dimensional (2D) or three-climensional …
An Integrated Framework For Learning And Reasoning, Christophe G. Giraud-Carrier, Tony R. Martinez
An Integrated Framework For Learning And Reasoning, Christophe G. Giraud-Carrier, Tony R. Martinez
Faculty Publications
Learning and reasoning are both aspects of what is considered to be intelligence. Their studies within AI have been separated historically, learning being the topic of machine learning and neural networks, and reasoning falling under classical (or symbolic) AI. However, learning and reasoning are in many ways interdependent. This paper discusses the nature of some of these interdependencies and proposes a general framework called FLARE, that combines inductive learning using prior knowledge together with reasoning in a propositional setting. Several examples that test the framework are presented, including classical induction, many important reasoning protocols and two simple expert systems.
Interview: Brenda Laurel, Jason Challas
Interview: Brenda Laurel, Jason Challas
SWITCH
This interview with Brenda Laurel, Virtual Reality (VR) author and thinker, discusses the applications and challenges of VR. Creating an emphatic experience using VR technology is possible, but the challenge lies in designing an environment that models the senses to stimulate emotions. VR enables experiences of different genders, but physiological differences between the sexes exist and are important to understand. However, technology used to create the environment and simulation of physical objects in VR is only in the developmental stage. Laurel believes in the importance of keeping the mind grounded in the physical body, in order to strengthen the appreciation …