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Abderrazzaq Kharroubi, Zouhair Ballouch, Rafika Hajji, Anass Yarroudh and Roland Billen
Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations o...
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Ahmed Skhiri, Ali Ferhi, Anis Bousselmi, Slaheddine Khlifi and Mohamed A. Mattar
A correct determination of irrigation water requirements necessitates an adequate estimation of reference evapotranspiration (ETo). In this study, monthly ETo is estimated using artificial neural network (ANN) models. Eleven combinations of long-term ave...
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Shaonan Hou, Chengjun Lin and Shaojun Yang
A transitive signature scheme enables anyone to obtain the signature on edge (??,??)
(
i
,
k
)
by combining the signatures on edges (??,??)
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j
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and (??,??)
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, but it suffers from signature theft and signature abuse. The existing work has...
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Mehdi Sadi, Bashir Mohammad Sabquat Bahar Talukder, Kaniz Mishty and Md Tauhidur Rahman
Universal adversarial perturbations are image-agnostic and model-independent noise that, when added to any image, can mislead the trained deep convolutional neural networks into the wrong prediction. Since these universal adversarial perturbations can se...
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Raza Nowrozy, Khandakar Ahmed, Hua Wang and Timothy Mcintosh
This paper proposed a novel privacy model for Electronic Health Records (EHR) systems utilizing a conceptual privacy ontology and Machine Learning (ML) methodologies. It underscores the challenges currently faced by EHR systems such as balancing privacy ...
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