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A probabilistic approach for human everyday activities recognition using body motion from RGB-D images
TLDR
We propose an approach that relies on cues from depth perception from RGB-D images, where features related to human body motion (3D skeleton features) are used on multiple learning classifiers in order to recognize human activities. Expand
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Extracting data from human manipulation of objects towards improving autonomous robotic grasping
TLDR
We study how humans manipulate simple daily objects, and construct a probabilistic representation model for the tasks and objects useful for autonomous grasping and manipulation by robotic hands. Expand
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A Study on CNN Transfer Learning for Image Classification
TLDR
This work proposes the study and investigation of such a CNN architecture model (i.e. Inception-v3) to establish whether it would work best in terms of accuracy and efficiency with new image datasets via Transfer Learning. Expand
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Social activity recognition based on probabilistic merging of skeleton features with proximity priors from RGB-D data
TLDR
We propose a probabilistic approach that merges spatio-temporal features from individual bodies and social features from the relationship between two individuals using proxemics theory to learn priors based on physical proximity. Expand
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Probabilistic human daily activity recognition towards robot-assisted living
TLDR
In this work, we present a human-centered robot application in the scope of daily activity recognition towards robot-assisted living. Expand
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Combining discriminative spatiotemporal features for daily life activity recognition using wearable motion sensing suit
TLDR
In this paper, we describe how to classify a set of human movements comprising daily activities using a wearable motion capture suit, denoted as FatoXtract. Expand
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Applying probabilistic Mixture Models to semantic place classification in mobile robotics
TLDR
In this paper a study is made of the problem of classifying scenarios, in terms of semantic categories, based on data gathered from sensors mounted on-board mobile robots operating indoors. Expand
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Stepping-stones to Transhumanism: An EMG-controlled Low-cost Prosthetic Hand for Academia
TLDR
This work intends to be a pioneer into developing a low-cost multipurpose robotic hand for research and academia. Expand
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A Deep Evolutionary Approach to Bioinspired Classifier Optimisation for Brain-Machine Interaction
TLDR
This study suggests a new approach to EEG data classification by exploring the idea of using evolutionary computation to both select useful discriminative EEG features and optimise the topology of Artificial Neural Networks. Expand
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A Study on Mental State Classification using EEG-based Brain-Machine Interface
TLDR
This work aims to find discriminative EEG-based features and appropriate classification methods that can categorise brainwave patterns based on their level of activity or frequency for mental state recognition useful for human-machine interaction. Expand
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