18 research outputs found
Detecting and recognizing centerlines as parabolic sections of the steerable filter response
Copyright 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is the accepted version of the article. The published version is available at
Simulation of a Texas Hold'Em poker player
Copyright 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is the accepted version of the article. The published version is available at
Pattern Spectra from Different Component Trees for Estimating Soil Size Distribution
We study the pattern spectra in context of soil structure analysis. Good soil structure is vital for sustainable crop growth. Accurate and fast measuring methods can contribute greatly to soil management decisions. However, the current in-field approaches contain a degree of subjectivity, while obtaining quantifiable results through laboratory techniques typically involves sieving the soil which is labour- and time-intensive. We aim to replace this physical sieving process through image analysis, and investigate the effectiveness of pattern spectra to capture the size distribution of the soil aggregates. We calculate the pattern spectra from partitioning hierarchies in addition to the traditional max-tree. The study is posed as an image retrieval problem, and confirms the ability of pattern spectra and suitability of different partitioning trees to re-identify soil samples in different arrangements and scales
An assessment of self-supervised learning for data efficient potato instance segmentation
Understanding Process Performance Measurement Systems
The purpose of this paper is to analyze the current state of Process Performance Measurement Systems (PPMS) by means of a systematic review of literature. The PPMS literature is reviewed using a systematic approach. Based on an extensive literature review only twelve articles that contain the term PPMS in the title were found. The literature analysis showed that PPMS is a relatively new topic in the area of performance measurement. In order to understand PPMS, it was crucial to explain the concepts of business process management, business performance measurement and Performance Measurement System (PMS) which are well known and used in the literature and practice. PPMS is a special type of PMS that should be used in process-oriented organizations. Limitations of this research lie in the fact that all the conclusions were derived only from the literature, not empirical research. The results presented in the paper continue towards providing an updated overview of the current state of performance measurement, especially PPMS in order to identify the existing research gaps on which ongoing and future research efforts regarding this topic can be focused