Universal conditional networks (UniCoN) for multi-age embryonic cartilage segmentation with sparsely annotated data by Nishchal Sapkota, Yejia Zhang, Zihao Zhao, Maria Jose Gomez, Yuhan Hsi, Jordan A. Wilson, Kazuhiko Kawasaki, Greg Holmes, Meng Wu, Ethylin Wang Jabs, Joan T. Richtsmeier, Susan M. Motch Perrine, Danny Z. Chen

“…While DL approaches have been proposed to automate cartilage segmentation, most such models have limited accuracy and generalizability, especially across data from different embryonic age groups. To address these limitations, we propose novel DL methods that can be adopted by any DL architectures—including Convolutional Neural Networks (CNNs), Transformers, or hybrid models—which effectively leverage age and spatial information to enhance model performance. …”
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EBSSPA: Efficient Deep Learning Model for Enhancing Blockchain Scalability and Security Through Fusion Pattern Analysis by Anuradha Hiwase, Amit Pimpalkar, Barkha Dange, Nitin Thakre, Sakshi Jaiswal, Tejaswini Mankar

“…Background: Blockchain technologies have come a long way, and integration of blockchain technologies into different fields is flourishing; however, there is a lack of blockchain platforms to manage the high network loads and more sophisticated security threats. …”
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Wireless Authentication Method Based on Near-Field Feature Fusion Network by QIU Jiefan, ZHOU Kezhong, ZHU Dongfu, ZHANG Jinhong, CHI Kaikai

“…Experimental results demonstrate that the proposed method outperforms existing identity recognition methods, confirming its effectiveness and robustness in different environments and under various conditions.…”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…Predictions for the different paths of the triplet are independently executed using feedforward neural networks. …”
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Analyzing infant cry to detect birth asphyxia using a hybrid CNN and feature extraction approach by Samrat Kumar Dey, Khandaker Mohammad Mohi Uddin, Arpita Howlader, Md. Mahbubur Rahman, Hafiz Md. Hasan Babu, Nitish Biswas, Umme Raihan Siddiqi, Badhan Mazumder

“…The performance of different ML and DL models is evaluated, with Logistic Regression (LR) achieving an accuracy of 99.16% and a 0.008% error rate. …”
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GLIHamba: global–local context image harmonization based on Mamba by Jinsheng SUN, Jiao PAN, Yu GUO, Chao YAO

“…In contrast, region-based matching methods treat the foreground and background regions as two different styles or domains. Although these methods achieve global consistency in harmonization results, they often overlook the spatial differences between the two regions. …”
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Application of Machine Learning to Statistical Evaluation of Artificial Rainfall Enhancement by Li Dan, Lin Wen, Liu Qun, Feng Hongfang, Hu Shuping, Wang Zhihai

“…In order to evaluate effects of artificial rainfall enhancement objectively and quantitatively, combing linear fitting, polynomial regression, spline regression and 3 other machine learning methods including decision tree, support vector machine and neural network, the relationship model between the rainfall in the target area and the contrast area is established based on rainfall data and operation information of recent 10 years in Fujian. Different historical regression statistical test schemes of rainfall enhancement effects are compared and analyzed, aiming to further optimize the best natural rainfall estimation algorithm based on alterable contrast area with statistical method, which can provide reference for the assessment of artificial rainfall enhancement effects. …”
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Development of Integrated Neural Network Model for Identification of Fake Reviews in E-Commerce Using Multidomain Datasets by Saleh Nagi Alsubari, Sachin N. Deshmukh, Mosleh Hmoud Al-Adhaileh, Fawaz Waselalla Alsaade, Theyazn H. H. Aldhyani

“…As this methodology uses different sizes of datasets, various input word-embedding matrices of n-gram features of the review’s text are developed and created with help of word-embedding layer that is one component of the proposed model. …”
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Coffee Leaf Rust Disease Detection and Implementation of an Edge Device for Pruning Infected Leaves via Deep Learning Algorithms by Raka Thoriq Araaf, Arkar Minn, Tofael Ahamed

“…Data collection was performed via two devices, a digital mirrorless camera and a phone camera, to diversify the dataset and test it with different datasets. The dataset, comprising a total of 2024 images, was divided into three sets with a ratio of 70% for training (1417 images), 20% for validation (405 images), and 10% for testing (202 images). …”
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Prediction of reduced left ventricular ejection fraction using atrial fibrillation or flutter electrocardiograms: A machine-learning study by Soonil Kwon, SooMin Chung, So-Ryoung Lee, Kwangsoo Kim, Junmo Kim, Dahyeon Baek, Hyun-Lim Yang, Eue-Keun Choi, Seil Oh

“…A hold-out test dataset was constructed using a different recruitment period. Five-fold cross-validation and calibration plots were used to evaluate performance. …”
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Ultrastructural analysis of the structure and distribution of the adherens junctions in the rats’ ventricular myocardium during postnatal stages of ontogeny after the infl uence of... by N. S. Petruk

“…Pairwise comparisons between means of different groups were performed using a Student t-test where, for each couple of normally distributed populations, the null hypothesis that the means are equal was verified. …”
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Comparing acoustic representations for deep learning-based classification of underwater acoustic signals: A case study on orca (Orcinus orca) vocalizations by Fabio Frazao, Ruth Joy, Michael Dowd

“…In general, we encourage developers working on similar tools to consider testing and combining different acoustic representations for improved classification performance.…”
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Study on the inversion and spatiotemporal variation mechanism of soil salinization at multiple depths in typical oases in arid areas: A case study of Wei-Ku Oasis by Jinming Zhang, Jianli Ding, Zihan Zhang, Jinjie Wang, Xu Zeng, Xiangyu Ge

“…Future research could also focus on more refined soil salinity mapping across seasons, obtaining more comprehensive driving data with higher temporal and spatial resolutions, analyzing the transfer mechanisms of soil salinity between different soil depths, and providing a theoretical basis for the scientific management of salinization.…”
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DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm by Abdulqader M. Almars

“…<b>Conclusions</b>: These results also show DeepGenMon’s effectiveness in accurately classifying different skin conditions, highlighting its potential as a reliable and low-resource tool in clinical settings.…”
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A fine-grained human facial key feature extraction and fusion method for emotion recognition by Shiwei Li, Jisen Wang, Linbo Tian, Jianqiang Wang, Yan Huang

“…Additionally, the comparative analysis shows that emotional features across different faces show similarities. Building on psychological research, we categorize the dataset into three emotion classes: positive, neutral, and negative. …”
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Knowledge Graph–Enhanced Deep Learning Model (H-SYSTEM) for Hypertensive Intracerebral Hemorrhage: Model Development and Validation by Yulong Xia, Jie Li, Bo Deng, Qilin Huang, Fenglin Cai, Yanfeng Xie, Xiaochuan Sun, Quanhong Shi, Wei Dan, Yan Zhan, Li Jiang

“…The HKG was exploited to guide the training of the semantic analysis and representation module and reasoning module, which makes the output of the H-SYSTEM more explainable.To assess the performance of the H-SYSTEM, we compared it with doctors and different large language models. ResultsThe outputs based on HKG showed reliable performance as compared with neurosurgical doctors, with an overall accuracy of 94.87%. …”
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Increasing comprehensiveness and reducing workload in a systematic review of complex interventions using automated machine learning by Olalekan A Uthman, Rachel Court, Jodie Enderby, Lena Al-Khudairy, Chidozie Nduka, Hema Mistry, GJ Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…The approach might also not be able to be used for other complex systematic reviews on different topics. Conclusion Our study shows that machine learning has the potential to significantly aid the labour-intensive screening of abstracts in systematic reviews of complex interventions. …”
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YOLOv8-eRFD-AP: A Novel Domain Generalization Model for UAV-Based Insulator Inspection Under Adverse Weather Conditions by Badr-Eddine Benelmostafa, Rita Aitelhaj, Hicham Medromi

“…Our model introduces a novel version of Robust Feature Downsampling (RFD) method, enhanced with Convolutional Block Attention Modules (CBAM) and Normalization Perturbation (NP) to preserve key spatial information and improve feature discrimination across different weather conditions. …”
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Concept of a geoinformation platform for landmines and other explosive objects detection and mapping with UAV by Mykhailo Popov, Sergey Stankevich, Sergey Mosov, Stanislav Dugin, Stanislav Golubov, Artem Andreiev, Artur Lysenko, Ievgen Saprykin

“…Future studies will involve extensive experimental testing and may involve convolutional neural networks (CNN) as a detection mechanism.…”
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Tree Species Detection and Enhancing Semantic Segmentation Using Machine Learning Models with Integrated Multispectral Channels from PlanetScope and Digital Aerial Photogrammetry i... by Arun Gyawali, Mika Aalto, Tapio Ranta

“…The study mainly involved two different objectives: first, tree species detection using the latest version of You Only Look Once (YOLOv12), and second, semantic segmentation (classification) using random forest, Categorical Boosting (CatBoost), and a Convolutional Neural Network (CNN). …”
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