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

“…However, reading CE examinations is a time-consuming task. Convolutional neural networks (CNNs) are highly efficient artificial intelligence tools for image analysis. …”
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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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Tumor detection in breast cancer pathology patches using a Multi-scale Multi-head Self-attention Ensemble Network on Whole Slide Images by Ruigang Ge, Guoyue Chen, Kazuki Saruta, Yuki Terata

“…Breast cancer (BC) is the most common type of cancer among women globally and is one of the leading causes of cancer-related deaths among women. …”
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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

“…To further analyze the frictional behavior, a deep learning model based on a one-dimensional convolutional neural network was employed to predict COF trends over time, achieving excellent accuracy with R² values of 0.9971 for validation and 0.9968 for testing. …”
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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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A Filter Theory of Photography by Ina Blom, Matthew Fuller

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

“…In this paper, ALL-diagnosing methods based on the convolutional autoencoder (CAE) was proposed to reduce the amount of data, and then convolutional neural network (CNN) was applied to identify ALL. …”
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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

“…This study employed a transfer learning approach using pre-trained convolutional neural networks (CNNs) alongside shallow machine learning algorithms (Support Vector Regression, XGBoost, Random Forest Regression) to estimate AGB. …”
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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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A lightweight multi-path convolutional neural network architecture using optimal features selection for multiclass classification of brain tumor using magnetic resonance images by Amreen Batool, Yung-Cheol Byun

“…Therefore, a lightweight Multi -path Convolutional Neural Network (M-CNN) is introduced to extract features using varying convolutional filters at each convolutional layer. …”
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