About: CNN-SVM Learning Approach Based Human Activity Recognition

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	CNN-SVM Learning Approach Based Human Activity Recognition
Creator	Alimi, Adel Basly, Hend Ouarda, Wael Ouni, Bouraoui Sayadi, Fatma
source	PMC
abstract	Although it has been encountered for a long time, the human activity recognition remains a big challenge to tackle. Recently, several deep learning approaches have been proposed to enhance the recognition performance with different areas of application. In this paper, we aim to combine a recent deep learning-based method and a traditional classifier based hand-crafted feature extractors in order to replace the artisanal feature extraction method with a new one. To this end, we used a deep convolutional neural network that offers the possibility of having more powerful extracted features from sequence video frames. The resulting feature vector is then fed as an input to the support vector machine (SVM) classifier to assign each instance to the corresponding label and bythere, recognize the performed activity. The proposed architecture was trained and evaluated on MSR Daily activity 3D dataset. Compared to state of art methods, our proposed technique proves that it has performed better.
has issue date	2020-06-05(xsd:dateTime)
bibo:doi	10.1007/978-3-030-51935-3_29
has license	no-cc
sha1sum (hex)	c29d9b3429f0f0f2c5f59d2049b3814c4f50a82b
schema:url	https://doi.org/10.1007/978-3-030-51935-3_29
resource representing a document's title	CNN-SVM Learning Approach Based Human Activity Recognition
has PubMed Central identifier	PMC7340932
schema:publication	Image and Signal Processing
resource representing a document's body	covid:c29d9b3429f0f0f2c5f59d2049b3814c4f50a82b#body_text
is schema:about of	named entity 'dataset' named entity 'enhance' named entity 'convolutional neural network' named entity 'performed' named entity 'performed' »more»

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