PokeME: Applying Context-Driven Notifications to Increase Worker Engagement in Mobile Crowd-Sourcing

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Laser Powder Bed Fusion (LPBF) is an Additive Manufacturing (AM) process consolidating parts layer by layer, from a metallic powder bed. It allows no limitation in terms of geometry and is therefore of particular interest to various industries. Metallic LP ...

Cars are some of the most security-critical consumer devices. On the one hand, owners expect rich infotainment features, including audio, hands-free calls, contact management, or navigation through their connected mobile phone. On the other hand, the infot ...

Background. In medicine and other applications, the copying and sharing of data is impractical for a range of well-considered reasons. With federated learning (FL) techniques, machine learning models can be trained on data spread across several locations w ...

Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision ...

The paper describes the submission of the team "We used bert!" to the shared task Gendered Pronoun Resolution (Pair pronouns to their correct entities). Our final submission model based on the fine-tuned BERT (Bidirectional Encoder Representations from Tra ...

Feature selection problems arise in a variety of applications, such as microarray analysis, clinical prediction, text categorization, image classification and face recognition, multi-label learning, and classification of internet traffic. Among the various ...

A fundamental problem arising in many areas of machine learning is the evaluation of the likelihood of a given observation under different nominal distributions. Frequently, these nominal distributions are themselves estimated from data, which makes them s ...

Data is pervasive in today's world and has actually been for quite some time. With the increasing volume of data to process, there is a need for faster and at least as accurate techniques than what we already have. In particular, the last decade recorded t ...

In recent years time series data has become ubiquitous thanks to affordable sensors and advances in embedded technology. Large amount of time-series data are continuously produced in a wide spectrum of applications, such as sensor networks, medical monitor ...

To improve the dexterity of multi-functional myoelectric prosthetic hand, more accurate hand gesture recognition based on surface electromyographic (sEMG) signal is needed. This paper evaluates two types of time-domain EMG features, one independent feature ...

Classifiers based on sparse representations have recently been shown to provide excellent results in many visual recognition and classification tasks. However, the high cost of computing sparse representations at test time is a major obstacle that limits t ...

Combining several classifiers has become a very active subdiscipline in the field of pattern recognition. For years, pattern recognition community has focused on seeking optimal learning algorithms able to produce very accurate classifiers. However, empiri ...

A brain-computer interface (BCI) is a system that enables control of devices or communication with other persons, only through cerebral activity, without using muscles. The main application for BCIs is assistive technology for disabled persons. Examples fo ...

The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...

Automatic facial action unit (AU) detection in videos is the key ingredient to all systems that utilize a subject face for either interaction or analysis purposes. With the ever growing range of possible applications, achieving a high accuracy in the simpl ...

Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...

Intrusion detection is frequently used as a second line of defense in Mobile Ad-hoc Networks (MANETs). In this paper we examine how to properly use classification methods in intrusion detection for MANETs. In order to do so we evaluate five supervised clas ...

Fisher kernels combine the powers of discriminative and generative classifiers by mapping the variable-length sequences to a new fixed length feature space, called the Fisher score space. The mapping is based on a single generative model and the classifier ...

The problem of time validity of biometric models has received only a marginal attention from researchers. In this paper, we investigate the aging influence on the classifier scores of genuine client. Our studies show that as age progresses the classifier s ...

Biometric authentication can be cast as a signal processing and statistical pattern recognition problem. As such, it relies on models of signal representations that can be used to discriminate between classes. One of the assumptions typically made by the p ...

PokeME: Applying Context-Driven Notifications to Increase Worker Engagement in Mobile Crowd-Sourcing

Chat with Graph Search

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

On the Insecurity of Vehicles Against Protocol-Level Bluetooth Threats

Weight Erosion: An Update Aggregation Scheme for Personalized Collaborative Machine Learning

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Transfer Learning from Pre-trained BERT for Pronoun Resolution

Theoretical foundations of forward feature selection methods based on mutual information

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization

Robust and Efficient Data Clustering with Signal Processing on Graphs

Distributed Time Series Analytics

EMG Pattern Recognition Using Decomposition Techniques for Constructing Multiclass Classifiers

Dictionary learning for fast classification based on soft-thresholding

Information theoretic combination of classifiers with application to face detection

Bayesian machine learning applied in a brain-computer interface for disabled users

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Improved Local Binary Pattern Based Action Unit Detection Using Morphological and Bilateral Filters

Prior knowledge in Kernel methods

Intrusion Detection in MANET Using Classification Algorithms: The Effects of Cost and Model Selection

A Multi-class Classification Strategy for Fisher Scores: Application to Signer Independent Sign Language Recognition

Identification of Aging Faces using A-stack Classification Model

Probabilistic models for multi-classifier biometric authentication using quality measures