Digital pathology and bioinformatics analysis of PIT1 expression in pituitary macroadenomas by Milić Marko Kimi, Sinanović Šćepan, Prodović Tanja

“…Digital histopathological images were obtained from a digital pathology repository, while RNA-seq data, including PIT1 gene expression, were retrieved from the NCBI GEO database. …”
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Employing sentinel-2 time-series and noisy data quality control enhance crop classification in arid environments: A comparison of machine learning and deep learning methods by Zahra Mohammadi Mobarakeh, Saeid Pourmanafi, Mohsen Ahmadi

“…Additionally, a neural network-based method was used to assess and enhance the quality of training data before modeling. …”
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Spatial Patterns in Fibrous Materials: A Metrological Framework for Pores and Junctions by Efi-Maria Papia, Vassilios Constantoudis, Youmin Hou, Prexa Shah, Michael Kappl, Evangelos Gogolides

“…Both patterns are characterized by peculiarities related to collinearity effects on neighboring points that cannot be captured by the conventional anisotropy analysis of point patterns. To characterize local collinearity, we develop a method that counts the number of collinear triplets of nearest neighbor points in a pattern and designs an appropriate parameter to quantify them, also applied to scanning electron microscopy (SEM) images of membranes, demonstrating consistency with simulated data.…”
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Video-Based Detection Infrastructure Enhancement for Automated Ship Recognition and Behavior Analysis by Xinqiang Chen, Lei Qi, Yongsheng Yang, Qiang Luo, Octavian Postolache, Jinjun Tang, Huafeng Wu

“…To bridge the gap, we proposed an ensemble you only look once (YOLO) framework for ship behavior analysis. First, we employed the convolutional neural network in the YOLO model to extract multi-scaled ship features from the input ship images. …”
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Assessing the Efficiency of Transformer Models with Varying Sizes for Text Classification: A Study of Rule-Based Annotation with DistilBERT and Other Transformers by Arafet Sbei, Khaoula ElBedoui, Walid Barhoumi

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MultiModal Ensemble Approach Leveraging Spatial, Skeletal, and Edge Features for Enhanced Bangla Sign Language Recognition by Khan Abrar Shams, Md. Rafid Reaz, Mohammad Ryan Ur Rafi, Sanjida Islam, Md. Shahriar Rahman, Rafeed Rahman, Md. Tanzim Reza, Mohammad Zavid Parvez, Subrata Chakraborty, Biswajeet Pradhan, Abdullah Alamri

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Hollows on Mercury: Creation and Analysis of a Global Reference Catalog With Deep Learning by Valentin T. Bickel, Ariel N. Deutsch, David T. Blewett

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Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

“…In terms of comparative performance, DL architectures like ResNet50, VGG16, and convolutional neural network demonstrated robust accuracy (95–99%) across diverse datasets, underscoring their effectiveness in managing complex image data. …”
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Development and validation of AI-based automatic segmentation and measurement of thymus on chest CT scans by Yusheng Guo, Bingxin Gong, Guowei Jiang, Wang Du, Shuangfeng Dai, Qi Wan, Dongyong Zhu, Chanyuan Liu, Yi Li, Qing Sun, Qianqian Fan, Bo Liang, Lian Yang, Chuansheng Zheng

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Sleep habits, brain functional networks, and type 2 diabetes risk: cohort studies from North American and Asian populations and mediating Mendelian randomization analyses by Faquan Hu, Qian Gong, Liyuan Xiong, Wei Zhao, Lingxiu Li, Yujiao Zheng

“…A correlation between the incidence of T2DM and increased connectivity in the default mode network (DMN), visual network (VN), central executive network, (CEN), and motor networks (MN) was found by MR analysis. …”
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Privacy preserving federated learning with convolutional variational bottlenecks by Daniel Scheliga, Patrick Mäder, Marco Seeland

“…To preserve the privacy preserving effect of PRECODE, our analysis reveals that variational modeling must be placed early in the network. …”
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Using deep learning for detecting BotCloud by Guang KOU, Guang-ming TANG, Shuo WANG, Hai-tao SONG, Yuan BIAN

“…Second, it mapped the basic network flow characteristics into gray image. Finally, in order to detect BotCloud, it utilized CNN algorithm to learn and extract characteristics that were more abstract to express the hidden model and structural relationship in the network data flow. …”
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A study on hybrid-architecture deep learning model for predicting pressure distribution in 2D airfoils by Jaehyun Yoon, Jaehyeok Doh

“…The proposed approach integrates both unsupervised and supervised learning paradigms, employing autoencoders (AE) for the unsupervised component and fully connected neural networks (FNN) for the supervised component. A surrogate model based on 2D image data was developed, enabling a comparative analysis of three distinct methods: the conventional AE, the convolutional autoencoder (CAE), and a hybrid CAE, which combines the CAE with a conventional AE. …”
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Traffic Pattern Analysis at Urban Intersections through Vehicle Detection in Aerial Imagery by R. Bahmanyar, J. Hellekes, M. Mühlhaus, V. Gstaiger, F. Kurz

“…This paper explores the application of aerial image sequences to analyze vehicle flows at urban intersections, with the goal of generating data that can inform adaptive traffic signal timing and improve urban mobility in complex, interconnected road networks. …”
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Disentangled Contrastive Learning From Synthetic Matching Pairs for Targeted Chest X-Ray Generation by Euyoung Kim, Soochahn Lee, Kyoung Mu Lee

“…These findings underscore the potential of our framework to improve medical imaging analysis and facilitate novel clinical applications.…”
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Application Analysis of Intelligent Robot Inspection System at Offshore Step-up Substation by Dengke ZHOU, Long CHENG, Yaping ZHANG, Peng TANG, Sheng GU, Kaiyuan ZHENG, Junsheng HE, Xue ZHANG

“…[Method] Firstly, a three-layer system architecture of the intelligent inspection system was designed, comprising perception-layer, network-layer and application-layer. Subsequently, detailed information about the robot inspection system was provided, including background management system, robot system design, communication power supply system design, and instrument image recognition technology. …”
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Runoff Coefficient Analysis After Regional Development in Tambakbayan Watershed, Yogyakarta, Indonesia by Slamet Suprayogi, M Widyastuti, M Pramono Hadi, Nugroho Christanto, Tommy Andryan Tivianton, Gita Oktaviani Fadhilah, Laelina Rahmawati, Lintang Nur Fadlillah

“…It used descriptive quantitative methods combining literature study and data calculation. The secondary data were obtained from digital land-use maps (RBI) in 2006 and 2017, SRTM images, soil types, and the drainage network of the watershed. …”
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Using Wavelet Analysis and Deep Learning for EMG-Based Hand Movement Signal Classification by Abdullah Erhan Akkaya, Harun Güneş

“…In this study; time series electromyography (EMG) data have been classified according to hand movements using wavelet analysis and deep learning. …”
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A deep learning based prediction model for effective elastic properties of porous materials by Chang Liu, Ran Guo, Yangming Su

“…This study provides a new method for predicting mechanical properties based on microstructure images. It has been verified that the mechanical properties directly predicted by the network are similar to the actual ones, with high accuracy and computational efficiency.…”
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Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature by Bosen Peng, Jiancheng Mu, Feng Xu, Wanyue Guo, Chuhuan Sun, Wei Fan

“…Major research topics include using various models to scan retinal images for diagnosing conditions such as age-related macular degeneration, diabetic retinopathy, and retinal nerve fiber layer thinning caused by glaucoma. …”
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