Data Mining - Concepts and Techniques.

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation which may be efficiently processed to determine correspondence. Applications of the interface and system include a VCR, medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

Ergonomic man-machine interface incorporating adaptive pattern recognition based control system

Computer and Robot Vision Vol. 1, by R.M. Haralick and Linda G. Shapiro, Addison-Wesley, 1992, ISBN 0-201-10887-1.

Computer and Robot Vision

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

/pdf/advances-in-spectral-spatial-classification-of-hyperspectral-vlt2ik4ef1.pdf

Advances in Spectral-Spatial Classification of Hyperspectral Images

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation that may be efficiently processed to determine correspondence. Applications of the interface and system include a video cassette recorder (VCR), medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

Adaptive pattern recognition based control system and method

The ‘Traffic Management as a Service’ (TMaaS) concept offers traffic management capabilities through a cloud-based platform. Without having to invest heavily in hardware, a city can simply subscribe to the platform in order to gain access to all available – multimodal and real-time – mobility-related data for their territory. TMaaS offers the tools to not only visualize data and manage traffic, but also to communicate with citizens. The platform automatically monitors the data flow and is able to send personalized messages to individual citizens, who in turn can reply to these messages and feed information back to the system. In this paper, we discuss the stakeholder research that was conducted and how it results in user-centred functional and design requirements for the TMaaS platform.

TMaaS: An Innovative, Multimodal and User-Centred Approach to Traffic Management

A method is explored to assess the quality of road network data based on image information in a reliable and accurate way. In the field of geography, an accuracy assessment method, called buffer-overlay-statistics, is known to assess the spatial quality of a line data set by using another line data set of higher spatial accuracy. Here, the method is adapted to assess the quality of a line data set based on image information rather than vector data. The average displacement accuracy measure is redefined, such that it is able to take into account line detection errors (fragmentation and noise). Experiments are conducted on artificial data showing how road extraction out of very high resolution satellite images can be used to asses the spatial accuracy of an existing road vector database.

Robust statistics for automated quality assessment of road network data based on VHR images

This paper deals with aggregate planning of Reconfigurable Assembly Lines (RAL). The assembly line considered in this paper consists of hexagonal cells. These have multiple slots where processing modules can be inserted to perform certain operations. In addition, each cell has a single central slot where a central module can be inserted for inter-cellular and intra-cellular transportation of parts. Multiple products with different assembly sequences must be handled over multiple planning periods. An Integer Quadratic Programming (IQP) model is proposed to solve the following problems simultaneously: (i) assigning processing modules and a central module to the cells; (ii) installation of the cells and conveyors between the cells; and (iii) routing products, ensuring that availability of the resources is not exceeded. The assembly line should be reconfigured over time to adapt to possible product functionality and demand changes at minimum reconfiguration, operational and material handling costs while ensuring the demand is met within each period. The IQP model is implemented and solved for an illustrative problem and its extensions using Gurobi.

Aggregate Planning for Multi-product Assembly Lines with Reconfigurable Cells

In this paper we demonstrate how the interaction between innovative methods in the field of computer vision and methods for multi-spectral image classification can help in extracting detailed land-cover / land-use information from Very High Resolution (VHR) satellite imagery. We introduce the novel concept of "geometric activity images", which we define as images encoding the strength of the relationship between a pixel and surrounding features detected through dedicated computer vision methods. These geometric activity images are used as alternatives to more traditional texture images that better describe the geometry of man-made structures and that can be included as additional information in a non-parametric supervised classification framework. We present a number of findings resulting from the integration of geometric activity images and multi-spectral bands in an artificial neural network classification. The geometric activity images we use result from the use of a ridge detector for straight line detection, calculated for different window sizes and for all multi-spectral bands and band-ratio images in a VHR scene. A selection of the most relevant bands to use for classification is carried out using band selection based on a genetic algorithm. Sensitivity analysis is used to assess the importance of each input variable. An application of the proposed methods to part of a Quickbird image taken over the suburban fringe of the city of Ghent (Belgium) shows that we are able to identify roads with much higher accuracy than when using more traditional multi-spectral image classification techniques.

Integrating geometric activity images in ANN classification

This paper investigates the mobility habits of electric bike owners as well as their preferred routes. Through a GPS tracking campaign conducted in the city of Ghent (Belgium) we analyze the mobility habits (travel distance, time spent, speed) during the week of some e-bike users. Moreover, we propose the results of our map matching, based on the Hausdorff criterion, and preliminary results on the route choice of our sample. We strongly believe that investigating the behavior of electric bikes’ owners can help us in better understanding how to incentivize the use of this mode of transport. First results show that the trips with a higher travel distance are performed during the working days. It could be easily correlated with the daily commuting trips (home-work). Moreover, the results of our map-matching highlight how 61% of the trips are performed using the shortest path.

https://biblio.ugent.be/publication/7029585/file/7038155.pdf

Sidharta Gautama

Papers

TMaaS: An Innovative, Multimodal and User-Centred Approach to Traffic Management

Robust statistics for automated quality assessment of road network data based on VHR images

Aggregate Planning for Multi-product Assembly Lines with Reconfigurable Cells

Integrating geometric activity images in ANN classification

Investigating the mobility habits of electric bike owners through GPS data