Search results for "pattern"
showing 10 items of 4203 documents
Data Mining in Cancer Research [Application Notes
2010
This article is not intended as a comprehensive survey of data mining applications in cancer. Rather, it provides starting points for further, more targeted, literature searches, by embarking on a guided tour of computational intelligence applications in cancer medicine, structured in increasing order of the physical scales of biological processes.
Dynamic Integration of Classifiers in the Space of Principal Components
2003
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble to be successful, it should consist of accurate and diverse base classifiers. However, it is also important that the integration procedure in the ensemble should properly utilize the ensemble diversity. In this paper, we present an algorithm for the dynamic integration of classifiers in the space of extracted features (FEDIC). It is based on the technique of dynamic integration, in which local accuracy estimates are calculated for each base classifier of an ensemble, in the neighborhood of a new instance to be pr…
Sequential Genetic Search for Ensemble Feature Selection
2005
Ensemble learning constitutes one of the main directions in machine learning and data mining. Ensembles allow us to achieve higher accuracy, which is often not achievable with single models. One technique, which proved to be effective for constructing an ensemble of diverse classifiers, is the use of feature subsets. Among different approaches to ensemble feature selection, genetic search was shown to perform best in many domains. In this paper, a new strategy GAS-SEFS, Genetic Algorithm-based Sequential Search for Ensemble Feature Selection, is introduced. Instead of one genetic process, it employs a series of processes, the goal of each of which is to build one base classifier. Experiment…
Iris : a solution for executing handwritten code
2012
Masteroppgave i informasjons- og kommunikasjonsteknologi IKT590 2012 – Universitetet i Agder, Grimstad This paper presents a novel approach to executing handwritten code, the solution coined Iris. My research falls within the field of mobile app development, handwriting recognition, optical and intelligent character recognition (OCR & ICR), machine learning, as well as various Computer Science-related fields such as domain specific languages, or DSLs. The solution outlined in this paper details a system where one can author code using only a writing utensil (such as a pen), scratch paper (such as a napkin), and a smart phone. Iris leverages the power of the cloud to process an image of hand…
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).