A Deep Learning Approach to Assist in Pottery Reconstruction from Its Sherds by Matheus Ferreira Coelho Pinho, Guilherme Lucio Abelha Mota, Gilson Alexandre Ostwald Pedro da Costa

“…Pottery is one of the most common and abundant types of human remains found in archaeological contexts. …”
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Automated detection of diabetic retinopathy lesions in ultra-widefield fundus images using an attention-augmented YOLOv8 framework by Lei-Si Hu, Jie Wang, Heng-Ming Zhang, Hai-Yu Huang

“…ObjectiveTo enhance the automatic detection precision of diabetic retinopathy (DR) lesions, this study introduces an improved YOLOv8 model specifically designed for the precise identification of DR lesions.MethodThis study integrated two attention mechanisms, convolutional exponential moving average (convEMA) and convolutional simple attention module (convSimAM), into the backbone of the YOLOv8 model. …”
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Assessment of a Hyperspectral Remote Sensing Model Performance for Particulate Phosphorus in Optically Shallow Lake Water by Banglong Pan, Wuyiming Liu, Zhuo Diao, Qianfeng Gao, Lanlan Huang, Shaoru Feng, Juan Du, Qi Wang, Jiayi Li, Jiamei Cheng

“…It also serves as one of the most significant sources of phosphorus for primary productivity, serving as a possible source of soluble reactive phosphorus, and contributing a sizable amount of the total phosphorus (TP), so monitoring the spatial and temporal variability of PP is crucial for understanding eutrophication in water bodies. …”
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Benchmarking CNN Architectures for Tool Classification: Evaluating CNN Performance on a Unique Dataset Generated by Novel Image Acquisition System by Muhenad Bilal, Ranadheer Podishetti, Daniel Grossmann, Markus Bregulla

“…Among the evaluated training strategies, fine-tuning proved the most efficient training method for developing CNN models for tool classification.…”
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Modeling the Relationship between Financial Stability and Banking Risks: Artificial Intelligence Approach by Hakeem Faraj Gumar, Parviz Piri, Mehdi Heydari

“…The variables of capital adequacy ratio, cash flow, bank size, and Z score were identified as the most important factors affecting financial stability. …”
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KOC_Net: Impact of the Synthetic Minority Over-Sampling Technique with Deep Learning Models for Classification of Knee Osteoarthritis Using Kellgren–Lawrence X-Ray Grade by Syeda Nida Hassan, Mudassir Khalil, Humayun Salahuddin, Rizwan Ali Naqvi, Daesik Jeong, Seung-Won Lee

“…One of the most common diseases afflicting humans is knee osteoarthritis (KOA). …”
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DNS over HTTPS Tunneling Detection System Based on Selected Features via Ant Colony Optimization by Hardi Sabah Talabani, Zrar Khalid Abdul, Hardi Mohammed Mohammed Saleh

“…Experimental results show that the proposed model selects the most effective features for both scenarios, achieving the highest detection and outperforming previous studies in IDS. …”
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Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic–Ischemic Encephalopathy Injury by Leah Twomey, Sergi Gomez, Emanuel Popovici, Andriy Temko

“…Using a nested cross-validation approach, an accuracy of 89.97% was achieved, in particular improving the AUC of the most challenging grades, Grade 1 and Grade 2, to 0.98 and 0.96. …”
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Performance Analysis of Eye Movement Event Detection Neural Network Models with Different Feature Combinations by Birtukan Adamu Birawo, Pawel Kasprowski

“…Event detection is the most important element of eye movement analysis. …”
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A Survey on Data Mining for Data-Driven Industrial Assets Maintenance by Eduardo Coronel, Benjamín Barán, Pedro Gardel

“…The survey also highlights the most frequently referenced data mining algorithms, such as the proportional hazard model, expert systems, support vector machines, random forest, autoencoder, and convolutional neural networks. …”
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An example of the application of artificial intelligence models in human resources processes by Mustafa Kemal Aydın, Berk Küçük, Selim Sürücü

“…In this context, the GRU model, which achieved an accuracy of 99%, provided the most superior result in this study and the literature. …”
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Study of the Current–Voltage Characteristics of Membrane Systems Using Neural Networks by Evgenia Kirillova, Anna Kovalenko, Makhamet Urtenov

“…This article is dedicated to the construction of neural networks for the prediction of the current–voltage characteristic (CVC). CVC is the most important characteristic of the mass transfer process in electro-membrane systems (EMS). …”
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Comparison of Machine Learning Methods for Menstrual Cycle Analysis and Prediction by Mutiara Khairunisa, Desak Made Sidantya Amanda Putri, I Gusti Ngurah Lanang Wijayakusuma

“…This study concludes that LSTM is the most effective model for menstrual cycle prediction. …”
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SKINVGG-NET: A MODIFIED AND FINE-TUNED VGG19-BASED DEEP LEARNING ARCHITECTURE FOR SKIN CANCER CLASSIFICATION by Maysaa R. Naeemah, Mohammed Y. Kamil

“…Skin cancer, one of the most common and potentially fatal cancers, requires early and correct diagnosis to improve patient outcomes. …”
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Quantifying the non-isomorphism of global urban road networks using GNNs and graph kernels by Linfang Tian, Weixiong Rao, Kai Zhao, Huy T. Vo

“…This finding challenges the claim that “GNNs are at most as powerful as the WL test in distinguishing graph structures.” …”
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Stock Closing Price Prediction with Machine Learning Algorithms: PETKM Stock Example In BIST by Abdullah Hulusi Kökçam, Gültekin Çağıl, Şevval Toprak

“…Random Forest Regression (RFR), Long-Short Term Memory (LSTM), and Convolutional Neural Network (CNN) algorithms are used in the prediction model. …”
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BN-SNN: Spiking neural networks with bistable neurons for object detection. by Siddiqui Muhammad Yasir, Hyun Kim

“…Spiking neural networks (SNNs) are emerging as a promising evolution in neural network paradigms, offering an alternative to conventional convolutional neural networks (CNNs). One of the most effective methods for SNN development is the CNN-to-SNN conversion process. …”
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Measuring Comparative Statistical Effectiveness of Cancer Subtype Categorization Using Gene Expression Data by Avila Clemenshia P., Deepa C.

“…When dealing with limited samples and high-dimensional biological data, most classifiers may suffer from overfitting and lower precision. …”
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Optimizing VGG16 Architecture with Bayesian Hyperparameter Tuning for Tomato Leaf Disease Classification by Tsaqif Muhammad Arkan, Aris Sugiharto, Helmie Arif Wibawa

“…The modified model integrates tunable parameters such as dropout rates, convolutional filters, and dense units, while maintaining the foundational structure of VGG16. …”
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BRAIN TUMOR DIAGNOSIS BASED ON MEDICAL IMAGES USING VISION TRANSFORMER by Masuma Mammadova, Fargana Abdullayeva

“… Brain tumor is one of the most common causes of death in modern times. Early and accurate detection of this disease can save the lives of a large part of the world’s population. …”
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