Search results for "Machine"

Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.

2020

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and &ldquo

Weakly supervised alignment of multisensor images

2015

Manifold alignment has become very popular in recent literature. Aligning data distributions prior to product generation is an appealing strategy, since it allows to provide data spaces that are more similar to each other, regardless of the subsequent use of the transformed data. We propose a methodology that finds a common representation among data spaces from different sensors using geographic image correspondences, or semantic ties. To cope with the strong deformations between the data spaces considered, we propose to add nonlineari-ties by expanding the input space with Gaussian Radial Basis Function (RBF) features with respect to the centroids of a partitioning of the data. Such featur…

Assessing the Impact of Temporary Retail Price Discounts Intervals Using SVM Semiparametric Regression

2009

Although the marketing literature has found that temporary retail price discounts cause a significant sales increase, little is known about the specific characteristics of deals that influence the magnitude of the sales spike. In this paper, we analyse the impact of the length of temporary retail price discounts periods on the sales increase using scanner-store daily-sales data for two frequently purchased product categories: ground coffee (a storable category) and yogurt (a perishable category).Wedevelop a robust semiparametric regression model based on support vector statistical theory with several previously proposed predictors along with a daily time description. This model also makes i…

Statistical formats to optimize evidence-based decision making: A behavioral approach

2013

Abstract Statistical information is crucial for managerial decision making. The decision-making literature in psychology and mathematical cognition documents how different statistical formats can facilitate certain types of decisions. The present analysis is the first of its kind to assess the impact of statistical formats in the presentation of data from market research on both the optimality of market decisions and the time required to perform the decision-making process. An economic experiment provides the data for this study. The experiment presents statistical information in simple frequencies and relative frequencies using numerical and pictorial representations in the context of diff…

The most human bot: Female gendering increases humanness perceptions of bots and acceptance of AI

2021

Using Support Vector Semiparametric Regression to estimate the effects of pricing on brand substitution

2008

A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes

2011

Published version of an article from the book: Hybrid artificial intelligent systems, Lecture notes in computer science. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-642-21219-2_2 There are numerous applications in Artificial Intelligence (AI) and Machine Learning (ML) where the criteria for decisions are based on testing procedures. The most common tools used in such random phenomena involve Random Walks (RWs). The theory of RWs and its applications have gained an increasing research interest since the start of the last century. [1]. In this context, we note that a RW is, usually, defined as a trajectory involving a series of successive ran…

Convolutional Neural Networks for Multispectral Image Cloud Masking

2020

Convolutional neural networks (CNN) have proven to be state of the art methods for many image classification tasks and their use is rapidly increasing in remote sensing problems. One of their major strengths is that, when enough data is available, CNN perform an end-to-end learning without the need of custom feature extraction methods. In this work, we study the use of different CNN architectures for cloud masking of Proba-V multispectral images. We compare such methods with the more classical machine learning approach based on feature extraction plus supervised classification. Experimental results suggest that CNN are a promising alternative for solving cloud masking problems.

Application of Genetic Algorithms to 3-D Shape Reconstruction in an Active Stereo Vision System

2001

In this paper, a new method for reconstructing 3-D shapes is proposed. It is based on an active stereo vision system composed of a camera and a light system which projects a set of structured laser rays on the scence to be analyzed. The depth information is provided by matching the laser rays and the corresponding spots appearing in the image. The matching task is performed by using Genetic Algorithms (GAs). The process converges towards the optimum solution which proves that GAs can effectively be used for this problem. An efficient 3-D reconstruction method is introduced. The experimental results demonstrate that the proposed approach is stable and provides high accuracy 3-D object recons…

Contrastive Learning with Continuous Proxy Meta-data for 3D MRI Classification

2021

Traditional supervised learning with deep neural networks requires a tremendous amount of labelled data to converge to a good solution. For 3D medical images, it is often impractical to build a large homogeneous annotated dataset for a specific pathology. Self-supervised methods offer a new way to learn a representation of the images in an unsupervised manner with a neural network. In particular, contrastive learning has shown great promises by (almost) matching the performance of fully-supervised CNN on vision tasks. Nonetheless, this method does not take advantage of available meta-data, such as participant’s age, viewed as prior knowledge. Here, we propose to leverage continuous proxy me…