In this paper, we propose an approach for corporate decision making with self-organizing patent maps labeled by technical terms and AHP. First, we select the patent area of interest and collect pertinent patent documents in text format. Second, we extract keywords by text mining to transform patent documents into feature vectors of the companies. Third, we input the feature matrix of technical ...

In this article we present an approach for the interactive retrieval of objects from databases that is based on the similarity of the objects. The considered objects are grouped based on their similarity to realise interactive associative search and visual exploration of the database. This enables a user to navigate through similar objects. If a textual description is available, the navigation,...

An art installation was on display in the Centre Pompidou National Museum of Modern Art in Paris, were visitors could contribute with their own personal objects, adding keyword descriptions and quantified semantic features such as age or hardness. The data was projected in real-time onto a Self-Organizing Map (SOM) and shown in the gallery. In this paper we analyze the same data by extracting v...

The distribution of a class of objects, such as images depicting a specific topic, can be studied by observing the best-matching units (BMUs) of the objects’ feature vectors on a Self-Organizing Map (SOM). When the BMU “hits” on the map are summed up, the class distribution may be seen as a two-dimensional histogram or discrete probability density. Due to the SOM’s topology preserving property,...

An adaptive two-stage approach is proposed for the classiication of surface defects. In the segmentation phase feature extraction is done and potential defect areas are marked. In the classiication phase features describing the shape and internal structure of defects are extracted and defects are classiied to diierent defect classes. The proposed segmentation scheme is taught with examples of f...

A large body of human image processing techniques use skin detection as a first primitive for subsequent feature extraction. Well established methods of colour modelling, such as histograms and Gaussian mixture models have enabled the construction of suitably accurate skin detectors. However such techniques are not ideal for use in adaptive real time environments. We describe methods of skin de...

In this paper we study how the Self-Organizing Map (SOM) can be used in analysing the structure of semantic concepts in visual data. We investigate two data sets with concept labels provided by humans, and unlabelled data for which we utilise automatically detected concept membership scores by using models trained on a labelled data set. By arranging the concept memberships of visual objects as...

A new training and recall method for self-organizing maps (SOM) is developed by comparison of SOM to the human information processing system. As neurons and cortical columns do not change their activity instantly, it is increased or decreased in a smooth way. This fact is introduced in SOM-neurons. In a same way, recognition of objects is supposed to be a task of analysing complete sets of feat...