Improving microvascular brain analysis with adversarial learning for OCT–TPM vascular domain translation by Nadia Badawi, Jaloliddin Rustamov, Zahiriddin Rustamov, Frederic Lesage, Nazar Zaki, Rafat Damseh

“…However, our statistical comparisons of vascular network features show the 3D model’s consistent superiority in generating vascular structures. …”
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Federated Deep Learning for Scalable and Explainable Load Forecasting in Privacy-Conscious Smart Cities by Ibrahim Alzamil

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EnviScan+: AI-driven plant identification and eco-system management for sustainable agriculture by Stitini Oumaima, Lachgar Mohamed, Bouleknadel Abderrahmane, Mandour Iyass

“…Its plant species recognition mechanism exploits convolutional neural networks (CNNs) trained on an extensive dataset for high accuracy, while the chatbot provides immediate explanations to plant species questions. …”
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A new method for identifying reservoir fluid properties based on well logging data: A case study from PL block of Bohai Bay Basin, North China by Song Jian, Zhang Hao, Guo Jianhong, Han Zihao, Guo Jianchao, Zhang Zhansong

“…In this article, an improved Markov variation field model is applied to map geophysical logging data and is integrated with a quantum hybrid neural network (HQNN) to address the nonlinear correlations between logging data. …”
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Machine Learning Models for Carbonation Depth Prediction in Reinforced Concrete Structures: A Comparative Study by Rafael Aredes Couto, Igor Augusto Guimarães Campos, Elvys Dias Reis, Daniel Hasan Dalip, Flávia Spitale Jacques Poggiali, Péter Ludvig

“…Model performances were evaluated across multiple scenarios, with compressive strength and exposure time identified as the most influential features, while relative humidity and exposure conditions had intermediate effects. …”
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GraphFedAI framework for DDoS attack detection in IoT systems using federated learning and graph based artificial intelligence by Mohd Anjum, Ashit Kumar Dutta, Ali Elrashidi, Sana Shahab, Asma Aldrees, Zaffar Ahmed Shaikh, Abeer Aljohani

“…Graph neural networks are utilized to extract both temporal and structural features from these graphs, thereby enhancing the accuracy of DDoS detection. …”
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Clinical Applicability and Cross-Dataset Validation of Machine Learning Models for Binary Glaucoma Detection by David Remyes, Daniel Nasef, Sarah Remyes, Joseph Tawfellos, Michael Sher, Demarcus Nasef, Milan Toma

“…Data preprocessing included resizing, normalization, and feature extraction to ensure consistency. Among the models, the deep neural network demonstrated the highest generalizability with stable performance across datasets, while the convolutional neural network showed moderate but consistent results. …”
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Opposition-Based White Shark Optimizer for Optimizing Modified EfficientNetV2 in Road Crack Classification by Mohammed Al-Shalabi, Mohammed A. Mahdi, Malik Braik, Mohammed Azmi Al-Betar, Shahanawaj Ahamad, Sawsan A. Saad

“…Although Convolutional Neural Networks (CNNs) and meta-heuristic algorithms have proven effective in solving real-world problems, their use in low-contrast pavement crack images is worth investigating. …”
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Achieving high-accuracy skin cancer classification with deep learning optimized by ant colony algorithm by Amany M. Sarhan, Hesham A. Ali, Shady Yasser, Mohamed Gobara, Ahmed A. Kandil, Ghada Sherif, Esraa Moustafa

“…We focus on utilizing deep learning, specifically convolutional neural networks (CNNs), to enhance the accuracy of skin lesion classification. …”
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Modeling residential property prices in emerging climate-responsive urban markets: a hybrid modeling framework for Baidoa City-Somalia by Mohamed Ibrahim Nor, Shuaib Nour Hussein

“…A hybrid-methods design was adopted, integrating a hedonic regression model with an artificial neural network (ANN) framework. The analysis utilizes a stratified random sample of 118 residential properties from the Baidoa Housing Survey, capturing diverse features such as property size, number of bedrooms, proximity to the central business district (CBD), safety, age, and air quality. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

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Optimized ReXNet variants with spatial pyramid pooling, CoordAttention, and convolutional block attention module for money plant disease detection by Parul Nasra, Jaibir Singh, Suman Rani, Gunjan Shandilya, Salil Bharany, Sandeep Sood, Ateeq Ur Rehman, Seada Hussen

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Utilizing CNN architectures for non-invasive diagnosis of speech disorders – further experiments and insights by Filip Ratajczak, Mikołaj Najda, Kamil Szyc

“…This research investigated the application of deep neural networks for diagnosing diseases that affect the voice and speech mechanisms through the non-invasive analysis of vowel sound recordings. …”
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INFORMATION MODELING OF ORGANIZATION OF BRIDGES’ CONSTRUCTION UNDER STOCHASTIC UNCERTAINTY OF TIME PARAMETERS by T. V. Bobrova, M. S. Ratanin, E. P. Timofeeva

“…The simulation is based on the generalized network model, calculated on the basis of the matrix (type of work - private work front) by the critical path method. …”
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A Multi-Class ECG Signal Classifier Using a Binarized Depthwise Separable CNN with the Merged Convolution–Pooling Method by Rui Zhang, Ranran Zhou, Zuting Zhong, Haifeng Qi, Yong Wang

“…In addition, the R peak interval data are integrated with P-QRS-T features to improve the classification accuracy. The proposed bDSCNN model is evaluated on an Intel DE1-SoC field-programmable gate array (FPGA), and the experimental results demonstrate that the proposed system achieves a five-class classification accuracy of 96.61% and a macro-F1 score of 89.08%, along with a dynamic power dissipation of 20 μW for five-category ECG signal classification. …”
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EOST-LSTM: Long Short-Term Memory Model Combined with Attention Module and Full-Dimensional Dynamic Convolution Module by Guangxin He, Wei Wu, Jing Han, Jingjia Luo, Lei Lei

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Astronomical Image Superresolution Reconstruction with Deep Learning for Better Identification of Interacting Galaxies by Jiawei Miao, Liangping Tu, Hao Liu, Jian Zhao

“…Galaxy–galaxy mergers are crucial in galaxy evolution, but the tidal features around galaxies are often faint, making it difficult to identify interacting or merging galaxies. …”
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Modern trends in diagnostics and prediction of results of anti-vascular endothelial growth factor therapy of pigment epithelial detachment in neovascular agerelated macular degener... by E. V. Kozina, S. N. Sakhnov, V. V. Myasnikova, E. V. Bykova, L. E. Aksenova

“…Modern technologies of spectral optical coherence tomography make it possible to evaluate detailed quantitative parameters of pigment epithelium detachment, such as height, width, maximum linear diameter, area, volume and refl ectivity within the detachment.Groups of Russian and foreign authors identify various biomarkers recorded on optical coherence tomography images. …”
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Prediction of Vanadium Contamination Distribution Pattern Through Remote Sensing Image Fusion and Machine Learning by Zipeng Zhao, Yuman Sun, Weiwei Jia, Jinyan Yang, Fan Wang

“…A dual-branch convolutional neural network (DB-CNN) fused hyperspectral and multispectral images and confirmed the fusion’s effectiveness. …”
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An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model by Rajesh Kannan Megalingam, Kariparambil Sudheesh Sankardas, Sakthiprasad Kuttankulangara Manoharan

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