Amel Ben Mahjoub

Amel Ben Mahjoub
University of Monastir | UTM · Department of Physics

PhD
Image recognition specialist

About

8
Publications
3,182
Reads
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54
Citations
Citations since 2017
6 Research Items
54 Citations
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2017201820192020202120222023051015

Publications

Publications (8)
Article
Full-text available
The application of Very-High-Resolution (VHR) satellites to survey cetaceans has gained considerable tractionover the last decade. Large whale species in particular lend themselves to detection by VHR imagery of ~0.50mresolution or less. Processing of satellite images can be manually intensive, and consequently artificial intelligencemethods are un...
Article
Action recognition is a very effective method of computer vision areas. In the last few years, there has been a growing interest in Deep learning networks as the Long Short–Term Memory (LSTM) architectures due to their efficiency in long-term time sequence processing. In the light of these recent events in deep neural networks, there is now conside...
Conference Paper
Full-text available
Deep learning is among the most commonly investigated approach in computer vision area. Quite recently, considerable attention has been paid to develop an end-to-end deep learning approach for action recognition. According to the developments of these time and resource consuming deep learning models, there is now a growing interest in implementing...
Article
Full-text available
Deep learning is widely considered to be the most important method in computer vision fields, which has a lot of applications such as image recognition, robot navigation systems and self-driving cars. Recent developments in neural networks have led to an efficient end-to-end architecture to human activity representation and classification. In the l...
Conference Paper
Full-text available
The recognition of human actions based on three-dimensional depth data has become a very active research field in computer vision. In this paper, we study the fusion at the feature and decision levels for depth data captured by a Kinect camera to improve action recognition. More precisely, from each depth video sequence, we compute Depth Motion Map...
Conference Paper
Full-text available
Human action recognition is an important computer vision research area, which is helpful in umpteen applications. This paper presents our method to recognize human activities. We use the Spatio-Temporal Interest Point (STIP) for detection of the important change in the image. Then, we extract appearance and motion features of these interest points...
Conference Paper
In this paper we combine two techniques in order to detect, track and identify person actions in a stream video. The combination of optical flow and stereovision allows also reconstructing the 3D shape of a scene from its 2D images. We take images from two cameras and match points to determine disparity, and therefore depth. The optical flow method...

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