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AdaBoostWikipedia

AdaBoost, short for Adaptive Boosting, is a machine learning meta-algorithm formulated by Yoav Freund and Robert Schapire, who won the 2003 Gödel Prize for their work. It can be used in conjunction with many other types of learning algorithms to improve performance. The output of the other learning algorithms ('weak learners') is combined into a weighted sum that represents the final output .

Data MiningEvaluation of Classifiers

Data Mining - Evaluation of Classifiers Lecturer: JERZY STEFANOWSKI Institute of Computing Sciences Poznan University of Technology Poznan, Poland

Training a better Haar and LBP cascade based Eye Detector

Object detection using Haar feature-based cascade classifiers is more than a decade and a half old. OpenCV framework provides a pre-built Haar and LBP based cascade classifiers for face and eye detection which are of reasonably good quality.

Data mining with WEKA, Part 2: Classification and clustering

Data mining is a collective term for dozens of techniques to glean information from data and turn it into meaningful trends and rules to improve your understanding of the data. In this second article of the series, we'll discuss two common data mining methods -- classification and clustering -- which can be used to do more powerful analysis on your data.

Hand Detection Using Cascade of Softmax Classifiers

Figure 1: The flowchart of window image classification using softmax-based cascade classifier. 3.3. Multiresolution HOG Feature for Different Stage-Classifiers . and all the rest are acquired using hard example mining techniques (Step (2.4)). Such strategy could enhance the discriminative ability of the first stage-classifier.

A Semisupervised Cascade Classification Algorithm

Applied Computational Intelligence and Soft Computing is a peer-reviewed, Open Access journal that focuses on the disciplines of computer science, engineering, and mathematics. The scope of the journal includes developing applications related to all aspects of natural and social sciences by employing the technologies of computational .

Mineral processingWikipedia

In the field of extractive metallurgy, mineral processing, also known as ore dressing, is the process of separating commercially valuable minerals from their ores Contents 1 History

Project 4: Face detection with a sliding window

Step 6 will depend on your particular strategy for mining hard negatives or building a classifier cascade. You are free to experiment with any stopping criteria. For instance, Dalal-Triggs only mines hard negatives once.

Hand Detection Using Cascade of Softmax Classifiers

Figure 1: The flowchart of window image classification using softmax-based cascade classifier. 3.3. Multiresolution HOG Feature for Different Stage-Classifiers . and all the rest are acquired using hard example mining techniques (Step (2.4)). Such strategy could enhance the discriminative ability of the first stage-classifier.

Mineral processingWikipedia

In the field of extractive metallurgy, mineral processing, also known as ore dressing, is the process of separating commercially valuable minerals from their ores Contents 1 History

classifier cascade for mininghotelsignature.

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A cascade of classifiers for extracting medication

Extracting medication information from clinical records has many potential applications, and recently published research, systems, and competitions reflect an interest therein. Much of the early extraction work involved rules and lexicons, but more recently machine learning has been applied to the .

Introduction to Data MiningProcess Mining

Introduction to Data Mining a.j.m.m. (ton) weijters . Overview • Why data mining (data cascade) • Application examples • Data Mining & Knowledge Discovering • Data Mining versus Process Mining /faculteit technologie management Why Data Mining . Classification (supervised) – Credit risk: result of data mining are rules that can be .

pythonCascade Classifiers for Multiclass Problems in

In the fit method of this meta classifier you subslice this data based on those classes and fit clones of the base_estimators for each level and store the resulting sub-classifiers at attribute of the meta classifier.

(PDF) Cascade Classifiers for Multiclass Problems

We discuss a cascade approach to multiclass classification problems which breaks the original task into smaller subproblems in a divide-and-conquer strategy.

Haar-feature Object Detection in C#CodeProject

The classification scheme used by the Viola-Jones method is actually a cascade of boosted classifiers. Each stage in the cascade is itself a strong classifier, in the sense it can obtain a really high rejection rate by combining a series of weaker classifiers in some fashion.

Fast Deep Convolutional Face Detection in the Wild

Fast Deep Convolutional Face Detection in the Wild Exploiting Hard Sample Mining . variable resolution, blurred image, etc. This issue was initially addressed either by using one classifier cascade for each specific facial view, , . This process simulates the hard negative sample mining procedure.

(PDF) A cascade of classifiers for extracting medication

The study also shows that a cascade of classifiers works better than a single classifier in extracting medication information. The system is available as is upon request from the first author .

Southern Cascades | WADNR

The two main mining areas in the Southern Cascades are the St. Helens and Washougal Mining Districts. Metal deposits are typically found in small fractures and veins within the rocks and contain predominantly: pyrite, magnetite, chalcopyrite, bornite, galena, and sphalerite; with lesser amounts of: copper, zinc, lead, molybdenum, gold, and silver.

Discriminative classifiers for image recognition

Attentional cascade of classifiers for fast rejection of non-face windows P. Viola and M. Jones. Rapid object detection using a boost ed cascade of simple features. CVPR 2001. P. Viola and M. Jones. Robust real-time face detection. . Data Mining and Knowledge Discovery, 1 f(x) .

Data Mining and ExplorationCaltech Astronomy

Data Mining and Exploration (a quick and very superficial intro) S. G. Djorgovski AyBi 199b, April 2011 . Cascade Correlation Joint DE, Naïve DE, Gauss/Joint DE, Gauss Naïve DE, . classification can be done is the effective limiting depth of your catalog - not the detection depth .

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