Computer-Aided Diagnosis of Acute Lymphoblastic Leukemiaby Using a Novel CAE-CNN Framework by Mohammed Mansoor Alhammadi

“…Therefore, fast and exact diagnosis is the most crucial factor for providing efficient management and treatment methods. …”
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Breast Tumor-Like-Masses Segmentation From Scattering Images Obtained With an Ultrahigh-Sensitivity Talbot-Lau Interferometer Using Convolutional Neural Networks by Ionut-Cristian Ciobanu, Nicoleta Safca, Elena Anghel, Dan Popescu

“…U-Net demonstrated the most stable performance with an accuracy of 86.34% and an F1-score of 90.2%, making it the most reliable model for tumor segmentation in scattering images. …”
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Detection and Severity Assessment of Parkinson’s Disease Through Analyzing Wearable Sensor Data Using Gramian Angular Fields and Deep Convolutional Neural Networks by Sayyed Mostafa Mostafavi, Shovito Barua Soumma, Daniel Peterson, Shyamal H. Mehta, Hassan Ghasemzadeh

“…Parkinson’s disease (PD) is the second-most common neurodegenerative disease. With more than 20,000 new diagnosed cases each year, PD affects millions of individuals worldwide and is most prevalent in the elderly population. …”
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Instantaneous 2D extreme wind speed prediction using the novel Wind Gust Prediction Net based on purely convolutional neural mechanism by Zeguo Zhang, Jianchuan Yin

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An Improved Decision Support System for Identification of Abnormal EEG Signals Using a 1D Convolutional Neural Network and Savitzky-Golay Filtering by Unmesh Shukla, Geetika Jain Saxena, Manish Kumar, Anil Singh Bafila, Amit Pundir, Sanjeev Singh

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Deep learning and capsule endoscopy: automatic identification and differentiation of small bowel lesions with distinct haemorrhagic potential using a convolutional neural network by Guilherme Macedo, Miguel José Mascarenhas Saraiva, João Afonso, Tiago Ribeiro, João Ferreira, Helder Cardoso, Ana Patricia Andrade, Marco Parente, Renato Natal, Miguel Mascarenhas Saraiva

“…Obscure gastrointestinal bleeding most often originates from the small bowel. CE frequently identifies a wide range of lesions with different bleeding potentials in these patients. …”
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Unobtrusive Sleep Posture Detection Using a Smart Bed Mattress with Optimally Distributed Triaxial Accelerometer Array and Parallel Convolutional Spatiotemporal Network by Zhuofu Liu, Gaohan Li, Chuanyi Wang, Vincenzo Cascioli, Peter W. McCarthy

“…Additionally, we have constructed a Parallel Convolutional Spatiotemporal Network (PCSN) by integrating Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bidirectional Long Short-Term Memory (Bi-LSTM) modules. …”
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An efficient trustworthy cyberattack defence mechanism system for self guided federated learning framework using attention induced deep convolution neural networks by Louai A. Maghrabi, Alanoud Subahi, Nouf Atiahallah Alghanmi, Turki Althaqafi, Nahla J. Abid, Nasser N. Albogami, Mahmoud Ragab

“…The Dung Beetle Optimization (DBO) technique is used in the feature selection process to identify the most relevant and non-redundant features. Furthermore, the fusion of convolutional neural networks, bidirectional long short-term memory, gated recurrent units, and attention (CBLG-A) models are employed to classify cyberattack defence mechanisms. …”
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Improved crop row detection by employing attention-based vision transformers and convolutional neural networks with integrated depth modeling for precise spatial accuracy by Hassan Afzaal, Derek Rude, Aitazaz A. Farooque, Gurjit S. Randhawa, Arnold W. Schumann, Nicholas Krouglicof

“…The proposed framework employs the latest attention and convolution-based encoders, such as ConvFormer, CAFormer, Swin Transformer, and ConvNextV2, in precisely identifying crop rows across varied and challenging agricultural environments. …”
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Deep Learning for Cardiovascular Disease Detection by Shivan H. Hussein, Najdavan A. Kako

“… Despite improvements, cardiovascular diseases (CVD) remain the most significant killer globally, accounting for around 17.9 million lives annually. …”
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Wear Characterization and Coefficient of Friction Prediction Using a Convolutional Neural Network Model for Chromium-Coated SnSb11Cu6 Alloy by Mihail Kolev, Vladimir Petkov, Veselin Petkov, Rositza Dimitrova, Shaban Uzun, Boyko Krastev

“…Feature importance analysis identified coating hardness as the most critical factor influencing COF and wear resistance, followed by matrix hardness near the coating. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…This paper presents an innovative approach using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model optimized by the Barnacles Mating Optimizer (BMO). …”
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Multi-component attention graph convolutional neural network for QoS-aware cloud job scheduling and resource management enhancing efficiency and performance in cloud computing by Deepak Dharrao, Sarika Deokate, Nagamma Hudgi, Shrinivas Shirkande, Vinod Mahajan, Madhuri Pangavhane, Anupkumar Bongale

“…Cloud computing is one of the most promising technologies for online business services, scheduling real-time cloud jobs with excellent Quality of Service (QoS) remains a challenge with current methodologies. …”
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Brittleness evaluation of main coal seams in Permian Taiyuan-Shanxi formations, Baode block, Ordos Basin: based on a convolutional neural network method by Qingfeng ZHANG, Ziling LI, Jikun ZHANG, Shuai HAO, Xiaoguang SUN, Yanjie SHANG, Yun ZUO

“…However, current methods mostly rely on empirical formulas, leading to limited evaluation accuracy. …”
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Using Nearest-Neighbor Distributions to Quantify Machine Learning of Materials’ Microstructures by Jeffrey M. Rickman, Katayun Barmak, Matthew J. Patrick, Godfred Adomako Mensah

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A Spatiotemporal Data Cube Approach to Classification of Variable Stars: A Catalog of Candidate Variable Stars from the TESS Full-frame Image Raw Data by Harry Qiang, Marina Kounkel, Sally Bass, Ryan Lingg, Logan Sizemore, Dylan Carroll, Brian Hutchinson, Keivan G. Stassun

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Predictive modelling employing machine learning, convolutional neural networks (CNNs), and smartphone RGB images for non-destructive biomass estimation of pearl millet (Pennisetum... by Faten Dhawi, Abdul Ghafoor, Norah Almousa, Sakinah Ali, Sara Alqanbar

“…Random Forest Regression performed best with the two most important features, whereas Support Vector Regression was the least effective. …”
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K-Means Clustering and Classification of Breast Cancer Images Using Histogram of Oriented Gradients Features and Convolutional Neural Network Models: Diagnostic Image Analysis Stud... by Said Salloum

“… Abstract BackgroundBreast cancer has proven to be the most common type of cancer among females around the world. …”
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MambaCAttnGCN+: a comprehensive framework integrating MambaTextCNN, cross-attention and graph convolution network for piRNA-disease association prediction by Dengju Yao, Xiangkui Li, Xiaojuan Zhan, Bo Zhang, Jian Zhang

“…A heterogeneous graph convolution method was then applied to identify potential associations between piRNAs and diseases, with cross-attention mechanisms further enhancing node features. …”
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BFER-Net: Babies Facial Expression Recognition Model Using ResNet12 Enabled Few-Shot Embedding Adaptation and Convolutional Block Attention Modules by Sumiya Arafin, Adnan Ferdous Ashrafi, Md. Golam Rabiul Alam, Ashis Talukder

“…Here, we have deployed the feature extraction process. A Convolutional Block Attention Module (CBAM) was integrated into the Modified ResNet12 architecture. …”
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