Drone hyperspectral imaging and artificial intelligence for monitoring moss and lichen in Antarctica by Juan Sandino, Johan Barthelemy, Ashray Doshi, Krystal Randall, Sharon A. Robinson, Barbara Bollard, Felipe Gonzalez

“…Data collected during a 2023 summer expedition to Antarctic Specially Protected Area 135, East Antarctica, were used to evaluate 12 configurations derived from five ML models, including gradient boosting (XGBoost, CatBoost) and convolutional neural networks (CNNs) (G2C-Conv2D, G2C-Conv3D, and UNet), tested with full and light input feature sets. …”
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Resultant Force on Grains of a Real Sand Dune: How to Measure It? by R. F. Miotto, C. A. Alvarez, D. S. Borges, W. R. Wolf, E. M. Franklin

“…Here, based on subaqueous experiments using a high‐speed camera, discrete numerical computations solving the motion at the grain scale, and a special training of a convolutional neural network, we show that it is, in fact, possible to estimate the resultant force acting on the grains of a barchan dune by using images. …”
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IEDSFAN: information enhancement and dynamic-static fusion attention network for traffic flow forecasting by Lianfei Yu, Ziling Wang, Wenxi Yang, Zhijian Qu, Chongguang Ren

“…Most of the existing traffic flow forecasting methods are static graph convolutional networks based on prior knowledge, ignoring the special spatial–temporal dynamics of spatial–temporal data. …”
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STL-DCSInformer-ETS: A Hybrid Model for Medium- and Long-Term Sales Forecasting of Fast-Moving Consumer Goods by Yecheng Ma, Lili He, Junhong Zheng

“…Meanwhile, the ETS model specializes in modeling seasonal patterns, further refining forecasting precision. …”
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Detection of Diabetic Retinopathy Using a Multi-Decision Inception-ResNet-Blended Hybrid Model by Santosh Kumar Henge, Nikhil Reddy Viraati, Musaed Alhussein, Ajay Shriram Kushwaha, Khursheed Aurangzeb, Ravleen Singh

“…The model undergoes thorough pre-processing and testing phases, utilizing eight layers of convolutions at each stage to handle various data matrices and integrate global and specialized features. …”
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Edge-Enhanced GCIFFNet: A Multiclass Semantic Segmentation Network Based on Edge Enhancement and Multiscale Attention Mechanism by Long Chen, Zhiyuan Qu, Yao Zhang, Jingyang Liu, Ruwen Wang, Dezheng Zhang

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F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection by Muhammad Rashid Minhas, Qaisar M. Shafi, Shoab Ahmed Khan, Tahir Ahmad, Subhan Ullah, Attaullah Buriro, Muhammad Azfar Yaqub

“…To tackle this, we propose the Fog-based One Solution For All (F-OSFA) system - a model with three specialized components. The first component uses a hybrid machine learning and deep learning framework that combines convolutional neural networks (CNNs) and decision trees to detect traditional DDoS attacks. …”
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Galaxy Spectroscopy without Spectra: Galaxy Properties from Photometric Images with Conditional Diffusion Models by Lars Doorenbos, Eva Sextl, Kevin Heng, Stefano Cavuoti, Massimo Brescia, Olena Torbaniuk, Giuseppe Longo, Raphael Sznitman, Pablo Márquez-Neila

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MSGEGA: Multiscale Gaussian Enhancement and Global-Aware Network for Infrared Small Target Detection by Yuyang Xi, Liuwei Zhang, Ying Jiang, Feng Qian, Fanjiao Tan, Qingyu Hou

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Gesture-controlled omnidirectional autonomous vehicle: A web-based approach for gesture recognition by Huma Zia, Bara Fteiha, Maha Abdulnasser, Tafleh Saleh, Fatima Suliemn, Kawther Alagha, Jawad Yousaf, Mohammed Ghazal

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Advanced image super-resolution using deep learning approaches by Mohamed Badiy, Fatima Amounas, Mourade Azrour, Mohammad Ali A. Hammoudeh

“…Specifically, we explore the integration of Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) to address the inherent challenges of producing high-quality images from low-resolution data. …”
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Analytic study and statistical enforcement of extended beta functions imposed by Mittag-Leffler and Hurwitz-Lerch Zeta functions by Faten F. Abdulnabi, Hiba F. Al-Janaby, Firas Ghanim

“…We use Mittag-Leffler and Hurwitz Lerch zeta (HLZ) kernels to produce the Beta function using the convolution tool. This special function advances a statistical implementation research approach. …”
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Evaluation of the precision and accuracy in the classification of breast histopathology images using the MobileNetV3 model by Kenneth DeVoe, Gary Takahashi, Ebrahim Tarshizi, Allan Sacker

“…Using transfer learning to take advantage of ImageNet embeddings without special feature extraction, we were able to correctly classify histopathology images broadly as benign or malignant with 0.98 precision, 0.97 recall, and an F1 score of 0.98. …”
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Models and methods for analyzing complex networks and social network structures by Ju. P. Perova, V. P. Grigoriev, D. O. Zhukov

“…Numerical modeling methods for analyzing complex networks and processes occurring in them are considered and described in detail. Special attention is paid to data processing in complex network structures using the Python language and its various available libraries.Results. …”
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Wireless Capsule Endoscopy Bleeding Images Classification Using CNN Based Model by Furqan Rustam, Muhammad Abubakar Siddique, Hafeez Ur Rehman Siddiqui, Saleem Ullah, Arif Mehmood, Imran Ashraf, Gyu Sang Choi

“…Imaging of the patient’s digestive tract through WCE produces a large dataset that requires a substantial amount of time and a special skill set from a medical practitioner for analysis. …”
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Deep Learning-Based Algorithms for Real-Time Lung Ultrasound Assisted Diagnosis by Mario Muñoz, Adrián Rubio, Guillermo Cosarinsky, Jorge F. Cruza, Jorge Camacho

“…Employing Convolutional Neural Networks (CNNs) trained on a semi-automatically annotated dataset, the model delineates these pulmonary patterns with the objective of enhancing diagnostic precision. …”
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Learning temporal granularity with quadruplet networks for temporal knowledge graph completion by Rushan Geng, Cuicui Luo

“…Simultaneously, it leverages Dynamic Convolutional Neural Networks (DCNNs) to extract representations of latent spaces across different temporal granularities. …”
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Enhancing Defect Detection on Surfaces Using Transfer Learning and Acoustic Non-Destructive Testing by Michele Lo Giudice, Francesca Mariani, Giosuè Caliano, Alessandro Salvini

“…Due to the great heterogeneity of materials and layering configurations, highly specialized expertise is often required to detect the presence and extent of such defects. …”
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Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review by Shaohua Wang, Dachuan Xu, Haojian Liang, Yongqing Bai, Xiao Li, Junyuan Zhou, Cheng Su, Wenyu Wei

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Sentiment analysis of pilgrims using CNN-LSTM deep learning approach by Aisha Alasmari, Norah Farooqi, Youseef Alotaibi

“…This paper provides a combination of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) algorithms for sentiment analysis of pilgrims using a novel and specialized dataset, namely Catering-Hajj. …”
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