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The level of dexterity of myoelectric hand prostheses depends to large extent on the feature representation and subsequent classification of surface electromyography signals. This work presents a comparison of various feature extraction and classification ...
Face-to-face interactions are part of everyday life, ranging from family to working in teams and to global communities. Social psychologists have long studied these interactions with the aim of understanding behavior, motivations, and emergence of interact ...
Face-to-face interactions are part of everyday life, ranging from family to working in teams and to global communities. Social psychologists have long studied these interactions with the aim of understanding behavior, motivations, and emergence of interact ...
One of the main challenge in non-native speech recognition is how to handle acoustic variability present in multiaccented non-native speech with limited amount of training data. In this paper, we investigate an approach that addresses this challenge by usi ...
This paper presents a novel method for classification of multilead electrocardiogram (ECG) signals. The feature extraction is based on the random projection (RP) concept for dimensionality reduction. Furthermore, the classification is performed by a neuro- ...
Recent studies suggest that advanced optimization based control methods such as model predictive control (MPC) can increase energy efficiency of buildings. However, adoption of these methods by industry is still slow, as building operators are used to work ...
This paper presents a novel method for classification of multi-lead electrocardiogram (ECG) signals. The feature extraction is based on the random projection (RP) concept for dimensionality reduction. Furthermore, the classification is performed by a neuro ...
Recent studies suggest that advanced optimization based control methods such as model predictive control (MPC) can increase energy efficiency of buildings. However, adoption of these methods by industry is still slow, as building operators are used to work ...
In this letter, an unsupervised kernel-based approach to change detection is introduced. Nonlinear clustering is utilized to partition in two a selected subset of pixels representing both changed and unchanged areas. Once the optimal clustering is obtained ...
In this paper we apply boosting to learn complex non-linear local visual feature representations, drawing inspiration from its successful application to visual object detection. The main goal of local feature descriptors is to distinctively repre- sent a s ...