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Gleice Kelly Barbosa Souza, Samara Oliveira Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos Oliveira, Daniela Carine Ramires Oliveira and Erivelton Geraldo Nepomuceno
Reinforcement learning is an important technique in various fields, particularly in automated machine learning for reinforcement learning (AutoRL). The integration of transfer learning (TL) with AutoRL in combinatorial optimization is an area that requir...
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David Naseh, Mahdi Abdollahpour and Daniele Tarchi
This paper explores the practical implementation and performance analysis of distributed learning (DL) frameworks on various client platforms, responding to the dynamic landscape of 6G technology and the pressing need for a fully connected distributed in...
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Hassen Louati, Ali Louati, Rahma Lahyani, Elham Kariri and Abdullah Albanyan
Responding to the critical health crisis triggered by respiratory illnesses, notably COVID-19, this study introduces an innovative and resource-conscious methodology for analyzing chest X-ray images. We unveil a cutting-edge technique that marries neural...
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Rito Clifford Maswanganyi, Chungling Tu, Pius Adewale Owolawi and Shengzhi Du
Transfer learning (TL) has been proven to be one of the most significant techniques for cross-subject classification in electroencephalogram (EEG)-based brain-computer interfaces (BCI). Hence, it is widely used to address the challenges of cross-session ...
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Mohamad Abou Ali, Fadi Dornaika and Ignacio Arganda-Carreras
Artificial intelligence (AI) has emerged as a cutting-edge tool, simultaneously accelerating, securing, and enhancing the diagnosis and treatment of patients. An exemplification of this capability is evident in the analysis of peripheral blood smears (PB...
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Mohamad Abou Ali, Fadi Dornaika and Ignacio Arganda-Carreras
Deep learning (DL) has made significant advances in computer vision with the advent of vision transformers (ViTs). Unlike convolutional neural networks (CNNs), ViTs use self-attention to extract both local and global features from image data, and then ap...
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Min-Kyung Lee and Inwon Lee
In this study, deep neural network (DNN) and transfer learning (TL) techniques were employed to predict the viscous resistance and wake distribution based on the positions of flow control fins (FCFs) applied to containerships of various sizes. Both metho...
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Samira Ardani, Saeed Eftekhar Azam and Daniel G. Linzell
Transfer Learning (TL) in structural health monitoring is used for generalizing the trained knowledge for damage identification of a group of similar structures. TL significantly reduces the computational cost associated with retraining Machine Learning ...
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Luigi Gianpio Di Maggio, Eugenio Brusa and Cristiana Delprete
The Intelligent Fault Diagnosis of rotating machinery calls for a substantial amount of training data, posing challenges in acquiring such data for damaged industrial machinery. This paper presents a novel approach for generating synthetic data using a G...
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Anfal Ahmed Aleidan, Qaisar Abbas, Yassine Daadaa, Imran Qureshi, Ganeshkumar Perumal, Mostafa E. A. Ibrahim and Alaa E. S. Ahmed
User authentication has become necessary in different life domains. Traditional authentication methods like personal information numbers (PINs), password ID cards, and tokens are vulnerable to attacks. For secure authentication, methods like biometrics h...
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