Search results for "ComputingMethodologies_PATTERNRECOGNITION"
showing 10 items of 296 documents
Table S1 from Open data and digital morphology
2017
Summary of main online repositories for 3D digital morphological data.
Interactive Pansharpening and Active Classification in Remote Sensing
2013
This chapter presents two multimodal prototypes for remote sensing image classification where user interaction is an important part of the system. The first one applies pansharpening techniques to fuse a panchromatic image and a multispectral image of the same scene to obtain a high resolution (HR) multispectral image. Once the HR image has been classified the user can interact with the system to select a class of interest. The pansharpening parameters are then modified to increase the system accuracy for the selected class without deteriorating the performance of the classifier on the other classes. The second prototype utilizes Bayesian modeling and inference to implement active learning …
A reliable and unbiased human protein network with the disparity filter
2017
AbstractThe living cell operates thanks to an intricate network of protein interactions. Proteins activate, transport, degrade, stabilise and participate in the production of other proteins. As a result, a reliable and systematically generated protein wiring diagram is crucial for a deeper understanding of cellular functions. Unfortunately, current human protein networks are noisy and incomplete. Also, they suffer from both study and technical biases: heavily studied proteins (e.g. those of pharmaceutical interest) are known to be involved in more interactions than proteins described in only a few publications. Here, we use the experimental evidence supporting the interaction between protei…
An exploration of semi-supervised text classification
2021
Master's thesis in Information- and communication technology (IKT590) Obtaining labeled data to train natural language machine learning algorithms is often expensive and time-consuming, while unlabeled data usually is free and easy to get. Frequently a large amount of labeled data is required by supervised learning to achieve good text classification performance. Semi-supervised learning (SSL) for text classification is an exciting area of research. SSL is a technique exploiting unlabeled and labeled data to achieve better classification performance than using labeled data alone and is particularly useful with limited labeled data. This thesis explores the impact of different parameters on …
Generative Adversarial Networks for Improving Face Classification
2017
Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Facial recognition can be applied in a wide variety of cases, including entertainment purposes and biometric security. In this thesis we take a look at improving the results of an existing facial recognition approach by utilizing generative adversarial networks to improve the existing dataset. The training data was taken from the LFW dataset[4] and was preprocessed using OpenCV[2] for face detection. The faces in the dataset was cropped and resized so every image is the same size and can easily be passed to a convolutional neural network. To the best of our knowledge no generative adversarial network…
Additional file 1 of Ethnobotany of the Aegadian Islands: safeguarding biocultural refugia in the Mediterranean
2021
Additional file 1. Ethnobiological uses of local taxa. Data table reporting the specific uses of local taxa documented in the present work and comparison to prior publications in the region. (.pdf file format).
Bioinformatics and Computational Biology
2009
Bioinformatics is a new, rapidly expanding field that uses computational approaches to answer biological questions (Baxevanis, 2005). These questions are answered by means of analyzing and mining biological data. The field of bioinformatics or computational biology is a multidisciplinary research and development environment, in which a variety of techniques from computer science, applied mathematics, linguistics, physics, and, statistics are used. The terms bioinformatics and computational biology are often used interchangeably (Baldi, 1998; Pevzner, 2000). This new area of research is driven by the wealth of data from high throughput genome projects, such as the human genome sequencing pro…
Improving the k-NCN classification rule through heuristic modifications
1998
Abstract This paper presents an empirical investigation of the recently proposed k-Nearest Centroid Neighbours ( k -NCN) classification rule along with two heuristic modifications of it. These alternatives make use of both proximity and geometrical distribution of the prototypes in the training set in order to estimate the class label of a given sample. The experimental results show that both alternatives give significantly better classification rates than the k -Nearest Neighbours rule, basically due to the properties of the plain k -NCN technique.
A new shape-oriented classification method for UV/VIS-spectra
1996
A new shape-oriented classification method is described. It is shown, how shapes of UV/VIS-spectra can be classified and coded and how a classification technique can be used to improve database search operations for pre-selections or even shape-oriented identifications.
Semi-supervised classification using tree-based self-organizing maps
2011
Published version of an article from the following onference prodeedings: AI 2011: Advances in Artificial Intelligence. Also available from the publisher on SpringerLink: http://dx.doi.org/10.1007/978-3-642-25832-9_3 This paper presents a classifier which uses a tree-based Neural Network (NN), and uses both, unlabeled and labeled instances. First, we learn the structure of the data distribution in an unsupervised manner. After convergence, and once labeled data become available, our strategy tags each of the clusters according to the evidence provided by the instances. Unlike other neighborhood-based schemes, our classifier uses only a small set of representatives whose cardinality can be m…