Journal ArticleDOI
A review on automatic image annotation techniques
TLDR
This paper analyzes key aspects of the various AIA methods, including both feature extraction and semantic learning methods and provides a comprehensive survey on automatic image annotation.About:
This article is published in Pattern Recognition.The article was published on 2012-01-01. It has received 472 citations till now. The article focuses on the topics: Image retrieval & Automatic image annotation.read more
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Book ChapterDOI
Support Vector Machine
TL;DR: This chapter simplifies the Lagrangian support vector machine approach using process diagrams and data flow diagrams to help readers understand theory and implement it successfully.
Posted Content
Understanding Random Forests: From Theory to Practice
TL;DR: The goal of this thesis is to provide an in-depth analysis of random forests, consistently calling into question each and every part of the algorithm, in order to shed new light on its learning capabilities, inner workings and interpretability.
Journal ArticleDOI
EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling
TL;DR: This paper develops a new ensemble construction algorithm (EUSBoost) based on RUSBoost, one of the simplest and most accurate ensemble, which combines random undersampling with Boosting algorithm, and proves that EUSBoost is able to outperform the state-of-the-art methods based on ensembles.
Journal ArticleDOI
A novel ensemble method for classifying imbalanced data
TL;DR: A novel ensemble method is proposed, which firstly converts an imbalanced data set into multiple balanced ones and then builds a number of classifiers on these multiple data with a specific classification algorithm, which usually performs better than the conventional methods on im balanced data.
Journal ArticleDOI
Plant Species Identification Using Computer Vision Techniques: A Systematic Literature Review
Jana Wäldchen,Patrick Mäder +1 more
TL;DR: This paper is the first systematic literature review with the aim of a thorough analysis and comparison of primary studies on computer vision approaches for plant species identification, identifying 120 peer-reviewed studies published in the last 10 years.
References
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Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Journal ArticleDOI
Classification and Regression Trees.
Book
C4.5: Programs for Machine Learning
TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
Journal ArticleDOI
Induction of Decision Trees
TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.
Journal ArticleDOI
Classification and regression trees
TL;DR: This article gives an introduction to the subject of classification and regression trees by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.