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Article ; Online: Lung pneumonia severity scoring in chest X-ray images using transformers.

Slika, Bouthaina / Dornaika, Fadi / Merdji, Hamid / Hammoudi, Karim

Medical & biological engineering & computing

2024

Abstract: To create robust and adaptable methods for lung pneumonia diagnosis and the assessment of its severity using chest X-rays (CXR), access to well-curated, extensive datasets is crucial. Many current severity quantification approaches require resource- ... ...

Abstract	To create robust and adaptable methods for lung pneumonia diagnosis and the assessment of its severity using chest X-rays (CXR), access to well-curated, extensive datasets is crucial. Many current severity quantification approaches require resource-intensive training for optimal results. Healthcare practitioners require efficient computational tools to swiftly identify COVID-19 cases and predict the severity of the condition. In this research, we introduce a novel image augmentation scheme as well as a neural network model founded on Vision Transformers (ViT) with a small number of trainable parameters for quantifying COVID-19 severity and other lung diseases. Our method, named Vision Transformer Regressor Infection Prediction (ViTReg-IP), leverages a ViT architecture and a regression head. To assess the model's adaptability, we evaluate its performance on diverse chest radiograph datasets from various open sources. We conduct a comparative analysis against several competing deep learning methods. Our results achieved a minimum Mean Absolute Error (MAE) of 0.569 and 0.512 and a maximum Pearson Correlation Coefficient (PC) of 0.923 and 0.855 for the geographic extent score and the lung opacity score, respectively, when the CXRs from the RALO dataset were used in training. The experimental results reveal that our model delivers exceptional performance in severity quantification while maintaining robust generalizability, all with relatively modest computational requirements. The source codes used in our work are publicly available at https://github.com/bouthainas/ViTReg-IP .
Language	English
Publishing date	2024-04-09
Publishing country	United States
Document type	Journal Article
ZDB-ID	282327-5
ISSN	1741-0444 ; 0025-696X ; 0140-0118
ISSN (online)	1741-0444
ISSN	0025-696X ; 0140-0118
DOI	10.1007/s11517-024-03066-3
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Article: SuperpixelGridMasks Data Augmentation: Application to Precision Health and Other Real-world Data.

Hammoudi, Karim / Cabani, Adnane / Slika, Bouthaina / Benhabiles, Halim / Dornaika, Fadi / Melkemi, Mahmoud

Journal of healthcare informatics research

2023 Volume 6, Issue 4, Page(s) 442–460

Abstract: A novel approach of data augmentation based on irregular superpixel decomposition is proposed. This approach called SuperpixelGridMasks permits to extend original image datasets that are required by training stages of machine learning-related analysis ... ...

Abstract	A novel approach of data augmentation based on irregular superpixel decomposition is proposed. This approach called SuperpixelGridMasks permits to extend original image datasets that are required by training stages of machine learning-related analysis architectures towards increasing their performances. Three variants named
Language	English
Publishing date	2023-01-13
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2895595-X
ISSN	2509-498X ; 2509-4971
ISSN (online)	2509-498X
ISSN	2509-4971
DOI	10.1007/s41666-022-00122-1
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Article: MaskedFace-Net - A dataset of correctly/incorrectly masked face images in the context of COVID-19.

Cabani, Adnane / Hammoudi, Karim / Benhabiles, Halim / Melkemi, Mahmoud

Smart health (Amsterdam, Netherlands)

2020 Volume 19, Page(s) 100144

Abstract: Wearing face masks appears as a solution for limiting the spread of COVID-19. In this context, efficient recognition systems are expected for checking that people faces are masked in regulated areas. Hence, a large dataset of masked faces is necessary ... ...

Abstract	Wearing face masks appears as a solution for limiting the spread of COVID-19. In this context, efficient recognition systems are expected for checking that people faces are masked in regulated areas. Hence, a large dataset of masked faces is necessary for training deep learning models towards detecting people wearing masks and those not wearing masks. Currently, there are no available large dataset of masked face images that permits to check if faces are correctly masked or not. Indeed, many people are not correctly wearing their masks due to bad practices, bad behaviors or vulnerability of individuals (e.g., children, old people). For these reasons, several mask wearing campaigns intend to sensitize people about this problem and good practices. In this sense, this work proposes an image editing approach and three types of masked face detection dataset; namely, the Correctly Masked Face Dataset (CMFD), the Incorrectly Masked Face Dataset (IMFD) and their combination for the global masked face detection (MaskedFace-Net). Realistic masked face datasets are proposed with a twofold objective: i) detecting people having their faces masked or not masked, ii) detecting faces having their masks correctly worn or incorrectly worn (e.g.; at airport portals or in crowds). To the best of our knowledge, no large dataset of masked faces provides such a granularity of classification towards mask wearing analysis. Moreover, this work globally presents the applied mask-to-face deformable model for permitting the generation of other masked face images, notably with specific masks. Our datasets of masked faces (137,016 images) are available at https://github.com/cabani/MaskedFace-Net. The dataset of face images Flickr-Faces-HQ3 (FFHQ), publicly made available online by NVIDIA Corporation, has been used for generating MaskedFace-Net.
Language	English
Publishing date	2020-11-28
Publishing country	Netherlands
Document type	Journal Article
ISSN	2352-6483
ISSN	2352-6483
DOI	10.1016/j.smhl.2020.100144
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Article ; Online: Towards the Next Generation of Full and Accurate 3D Building Models by Fusing Aerial and Terrestrial Imagery

Karim Hammoudi

International Journal of Computer Science Issues, Vol 9, Iss 2, Pp 475-

2012 Volume 476

Abstract: Nowadays, the 3D city modeling is an emerging field of great interest to the broad community of computer science researchers. This paper concisely describes the content of recently defended thesis works dealing with various aspects of 3D city modeling ( ... ...

Abstract	Nowadays, the 3D city modeling is an emerging field of great interest to the broad community of computer science researchers. This paper concisely describes the content of recently defended thesis works dealing with various aspects of 3D city modeling (short abstract of Ph.D. Thesis). More specifically, the Ph.D. dissertation was entitled “Contributions to the 3D city modeling: 3D polyhedral building model reconstruction from aerial images and 3D facade modeling from terrestrial 3D point cloud and images”.
Keywords	3D City Modeling ; Building Roof Reconstruction ; Urban Facade Modeling and Texturing ; Mobile Mapping System ; Calibrated Images ; 3D Point Cloud. ; IJCSI ; Electronic computers. Computer science ; QA75.5-76.95 ; Instruments and machines ; QA71-90 ; Mathematics ; QA1-939 ; Science ; Q ; DOAJ:Computer Science ; DOAJ:Technology and Engineering
Language	English
Publishing date	2012-03-01T00:00:00Z
Publisher	IJCSI Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Personalized Shares in Visual Cryptography

Karim Hammoudi / Mahmoud Melkemi

Journal of Imaging, Vol 4, Iss 11, p

2018 Volume 126

Abstract: This article deals with visual cryptography. It consists of hiding a message in two key images (also called shares). The decryption of the message is obtained through human vision by superposition of the shares. In existing methods, the surface of key ... ...

Abstract	This article deals with visual cryptography. It consists of hiding a message in two key images (also called shares). The decryption of the message is obtained through human vision by superposition of the shares. In existing methods, the surface of key images is not visually pleasant and is not exploited for communicating textual or pictorial information. Presently, we propose a pictogram-based visual cryptography technique, which generates shares textured with customizable and aesthetic rendering. Moreover, robustness characteristics of this technique to the automated decoding of the secret message are presented. Experimental results show concrete personalized shares and their applicative potentials for security and creative domains.
Keywords	visual cryptography ; visual representation ; visual communication ; visual effect ; graphic design ; pictogram ; pixel art ; negative space ; texture mapping ; visualization ; Photography ; TR1-1050 ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	700
Language	English
Publishing date	2018-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Mechanical and Microstructural Properties of Ordinary Concrete with High Additions of Crushed Glass.

Belebchouche, Cherif / Moussaceb, Karim / Bensebti, Salah-Eddine / Aït-Mokhtar, Abdelkarim / Hammoudi, Abdelkader / Czarnecki, Slawomir

Materials (Basel, Switzerland)

2021 Volume 14, Issue 8

Abstract: This study investigates the use of crushed glass waste as partial cement replacement in ordinary concretes. Six concrete mixes were designed and prepared: a reference without substitution and five substitution percentages of crushed glass waste ranging ... ...

Abstract	This study investigates the use of crushed glass waste as partial cement replacement in ordinary concretes. Six concrete mixes were designed and prepared: a reference without substitution and five substitution percentages of crushed glass waste ranging from 5% to 25%. The made concrete mix design underwent different tests, namely: slump test, mechanical strength, thermogravimetric analysis (TGA), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) determination and finally, water porosimetry, in order to evaluate the influence of the use of crushed glass waste on the properties of fresh and hardened concrete. Mechanical strengths results show that the use of 15% of the crushed glass waste improves the mechanical strength. TGA analysis confirms this result by highlighting a higher hydration degree. The latter contributes to the reduction of the porosity and, consequently, the mechanical strength increases. Also, it can be caused by the increasing amount of chromium which, if added a little, accelerates the hydration of C3S and leads to an increase of the mechanical strength. The BET technique and porosimetry tests showed that the use of crushed glass waste reduces the global porosity of concrete. This is due to the filling effect of the glass powder.
Language	English
Publishing date	2021-04-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2487261-1
ISSN	1996-1944
ISSN	1996-1944
DOI	10.3390/ma14081872
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Book ; Online: Validating the correct wearing of protection mask by taking a selfie

Hammoudi, Karim / Cabani, Adnane / Benhabiles, Halim / Melkemi, Mahmoud

design of a mobile application "CheckYourMask'' to limit the spread of COVID-19

2020

Abstract: In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019-20 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) ... ...

Abstract	In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019-20 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting to everyone having a smartphone and being able to take a picture to verify that his/her protection mask is correctly positioned on his/her face. Such application can be particularly useful for people using face protection mask for the first time and notably for children and old people. The designed method exploits Haar-like feature descriptors to detect key features of the face and a decision-making algorithm is applied. Experimental results show the potential of this method in the validation of the correct mask wearing. To the best of our knowledge, our work is the only one that currently proposes a mobile application design ``CheckYourMask'' for validating the correct wearing of protection mask.
Keywords	covid19
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Publishing country	us
Document type	Book ; Online
DOI	10.36227/techrxiv.12355970
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Validating the correct wearing of protection mask by taking a selfie

Hammoudi, Karim / Cabani, Adnane / Benhabiles, Halim / Melkemi, Mahmoud

design of a mobile application "CheckYourMask'' to limit the spread of COVID-19

2020

Abstract	In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019-20 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting to everyone having a smartphone and being able to take a picture to verify that his/her protection mask is correctly positioned on his/her face. Such application can be particularly useful for people using face protection mask for the first time and notably for children and old people. The designed method exploits Haar-like feature descriptors to detect key features of the face and a decision-making algorithm is applied. Experimental results show the potential of this method in the validation of the correct mask wearing. To the best of our knowledge, our work is the only one that currently proposes a mobile application design ``CheckYourMask'' for validating the correct wearing of protection mask.
Keywords	covid19
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Publishing country	us
Document type	Book ; Online
DOI	10.36227/techrxiv.12355970.v1
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: SuperpixelGridCut, SuperpixelGridMean and SuperpixelGridMix Data Augmentation

Hammoudi, Karim / Cabani, Adnane / Slika, Bouthaina / Benhabiles, Halim / Dornaika, Fadi / Melkemi, Mahmoud

2022

Abstract	A novel approach of data augmentation based on irregular superpixel decomposition is proposed. This approach called SuperpixelGridMasks permits to extend original image datasets that are required by training stages of machine learning-related analysis architectures towards increasing their performances. Three variants named SuperpixelGridCut, SuperpixelGridMean and SuperpixelGridMix are presented. These grid-based methods produce a new style of image transformations using the dropping and fusing of information. Extensive experiments using various image classification models and datasets show that baseline performances can be significantly outperformed using our methods. The comparative study also shows that our methods can overpass the performances of other data augmentations. Experimental results obtained over image recognition datasets of varied natures show the efficiency of these new methods. SuperpixelGridCut, SuperpixelGridMean and SuperpixelGridMix codes are publicly available at https://github.com/hammoudiproject/SuperpixelGridMasks Comment: The project is available at https://github.com/hammoudiproject/SuperpixelGridMasks
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Artificial Intelligence ; Computer Science - Information Retrieval ; Computer Science - Machine Learning ; 65D18 ; 94A08 ; I.4 ; I.2
Subject code	006
Publishing date	2022-04-11
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: MaskedFace-Net -- A Dataset of Correctly/Incorrectly Masked Face Images in the Context of COVID-19

Cabani, Adnane / Hammoudi, Karim / Benhabiles, Halim / Melkemi, Mahmoud

2020

Abstract: The wearing of the face masks appears as a solution for limiting the spread of COVID-19. In this context, efficient recognition systems are expected for checking that people faces are masked in regulated areas. To perform this task, a large dataset of ... ...

Abstract	The wearing of the face masks appears as a solution for limiting the spread of COVID-19. In this context, efficient recognition systems are expected for checking that people faces are masked in regulated areas. To perform this task, a large dataset of masked faces is necessary for training deep learning models towards detecting people wearing masks and those not wearing masks. Some large datasets of masked faces are available in the literature. However, at the moment, there are no available large dataset of masked face images that permits to check if detected masked faces are correctly worn or not. Indeed, many people are not correctly wearing their masks due to bad practices, bad behaviors or vulnerability of individuals (e.g., children, old people). For these reasons, several mask wearing campaigns intend to sensitize people about this problem and good practices. In this sense, this work proposes three types of masked face detection dataset; namely, the Correctly Masked Face Dataset (CMFD), the Incorrectly Masked Face Dataset (IMFD) and their combination for the global masked face detection (MaskedFace-Net). Realistic masked face datasets are proposed with a twofold objective: i) to detect people having their faces masked or not masked, ii) to detect faces having their masks correctly worn or incorrectly worn (e.g.; at airport portals or in crowds). To the best of our knowledge, no large dataset of masked faces provides such a granularity of classification towards permitting mask wearing analysis. Moreover, this work globally presents the applied mask-to-face deformable model for permitting the generation of other masked face images, notably with specific masks. Our datasets of masked face images (137,016 images) are available at https://github.com/cabani/MaskedFace-Net.
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Electrical Engineering and Systems Science - Image and Video Processing ; covid19
Subject code	006
Publishing date	2020-08-18
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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