MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

Principal component analysis is one of the most important and powerful methods in chemometrics as well as in a wealth of other areas. This paper provides a description of how to understand, use, and interpret principal component analysis. The paper focuses on the use of principal component analysis in typical chemometric areas but the results are generally applicable.

/pdf/principal-component-analysis-1sba76ou47.pdf

Principal component analysis

A matter of life and death.

Application of response surface methodology and artificial neural network methods in modelling and optimization of biosorption process.

The utilization of leaf-based adsorbents for dyes removal: A review

Thomas and artificial neural network models for the fixed-bed adsorption of methylene blue by a beach waste Posidonia oceanica (L.) dead leaves

http://facweb.cs.depaul.edu/research/vc/medix/2008/seminar/SelverPatientOrientedAndRobustAutomaticLiverSegmentation.pdf

Patient oriented and robust automatic liver segmentation for pre-evaluation of liver transplantation

Online local learning algorithms for linear discriminant analysis

We extend Sandholm's bidtree-based IDA* algorithm for combinatorial auction winner determination to deal with negotiation over tasks with precedence constraints. We evaluate its performance, and show that the order of items in the bidtree has a major impact on performance. Specifically, performance is enhanced if the items with the largest numbers of bids are at the top of the bidtree. This is due to the fact that the effective branching factor in the search tree is controlled by the number of bids returned from a query to the bidtree, which in turn is strongly related to its construction.

Bidtree Ordering in IDA* Combinatorial Auction Winner-Determination with Side Constraints

Booster biocides have negative impacts on marine organisms and it is therefore essential to monitor their toxicity prior to their use in antifouling paints. In this study, we describe a method for improving the reliability of a well-used acute toxicity test. We studied a model organism, Artemia salina, by using a novel video tracking method. Acute toxicities of a reference toxicant (potassium dichromate) and a potential toxicant (p-coumaric acid) were examined for newly hatched A. salina nauplii. Survival percentage, swimming velocity, and paths covered by nauplii were determined with the new algorithm. A. salina nauplii were affected by both tested toxicants, an outcome clearly detected by the algorithm. The results demonstrate that the video tracking algorithm could be used for testing the acute toxicities of booster biocides as well as other potential toxicants on A. salina. With slight modifications, it could be used for testing other similar aquatic micro-organisms. This report has linked video seque...

Güleser Kalaycı Demir

Papers

Thomas and artificial neural network models for the fixed-bed adsorption of methylene blue by a beach waste Posidonia oceanica (L.) dead leaves

Patient oriented and robust automatic liver segmentation for pre-evaluation of liver transplantation

Online local learning algorithms for linear discriminant analysis

Bidtree Ordering in IDA* Combinatorial Auction Winner-Determination with Side Constraints

A video tracking based improvement of acute toxicity test on Artemia salina