Lightweight Football Motion Recognition and Intensity Analysis Using Low-Cost Wearable Sensors by Qian Xie, Ning Jin, Shanshan Lu

“…The model can perform classification and regression tasks in parallel and output the results simultaneously. A feature extraction scheme is designed in the initial data processing, and feature data augmentation is performed to solve the small sample data problem. …”
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A GAN-Based Framework with Dynamic Adaptive Attention for Multi-Class Image Segmentation in Autonomous Driving by Bashir Sheikh Abdullahi Jama, Mehmet Hacibeyoglu

“…It does this by allowing the discriminator network in GAN to evaluate the segmentation mask created by the generator. …”
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ECGConVT: A Hybrid CNN and Vision Transformer Model for Enhanced 12-Lead ECG Images Classification by Mudassar Khalid, Charnchai Pluempitiwiriyawej, Abdulkadhem A. Abdulkadhem, Imran Afzal, Tien Truong

“…We propose ECGConVT framework that combines Convolutional Neural Network (CNN) module for extracting local features, and Vision Transformer (ViT) module for capturing global features. …”
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DSR-YOLO: A lightweight and efficient YOLOv8 model for enhanced pedestrian detection by Mustapha Oussouaddi, Omar Bouazizi, Aimad El mourabit, Zine el Abidine Alaoui Ismaili, Yassine Attaoui, Mohamed Chentouf

“…This paper presents DSR-YOLO, a pedestrian detection network that addresses critical challenges, such as scale variations and complex backgrounds. …”
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PathCare: Integrating Clinical Pathway Information to Enable Healthcare Prediction at the Neuron Level by Dehao Sui, Lei Gu, Chaohe Zhang, Kaiwei Yang, Xiaocui Li, Liantao Ma, Ling Wang, Wen Tang

“…PathCare employs an auxiliary sub-network that models future visit patterns to capture temporal health progression, coupled with a neuron-level filtering gate that adaptively selects relevant features while filtering out redundant information. …”
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An Integrated Framework for Real-Time Sea-State Estimation of Stationary Marine Units Using Wave Buoy Analogy by Hamed Majidiyan, Hossein Enshaei, Damon Howe, Yiting Wang

“…The current study builds on previous work, aiming to propose an AI framework to reduce the estimation time lag between exciting waves and respective estimation by transforming temporal/spectral features into a manipulated scalogram. For that, an adaptive ship response predictor and deep learning model were incorporated to classify seaway while minimizing network complexity through feature engineering. …”
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IBCFaiCDR: Auxiliary data-driven item-based collaborative filtering in cross-domain RSs to address user cold start problem by Ronakkumar Patel, Priyank Thakkar

“…The suggested collaborative filtering technique employs IBCF which uses the item similarity obtained with item features. These features are generated by the proposed approach IBCFaiCDR's model, trained on source domain data such as product images and reviews. …”
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Detección de situaciones de emergencias usando el modelo Naive- Bayes de machine learning. by Iván Leonel Vásquez-Rojas, Miguel José Vívas-Cortéz

“…Nowadays, social networks have gained ground in the generation and obtaining of information instantly, this feature makes it very useful in the detection and warnings of emergencies such as road accidents, fires, storms, floods, etc. …”
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Intention Recognition of AAV Swarm Based on GAT-EPool-BiGRU Model by Jiajun Yuan, Xiang Jia, Yu An, Liang Geng, Lei Shu

“…Addressing the limitations of existing methods—such as the low feature transfer efficiency of stacked autoencoders (SAE) and the tendency of panoramic convolutional long short-term memory networks (PC-LSTM) to lose tactical details—this paper proposes a novel deep learning model called GAT-EPool-BiGRU, which integrates Graph Attention Networks (GAT), Edge Pooling (EPool), and Bidirectional Gated Recurrent Units (BiGRU). …”
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A novel approach for breast cancer detection using a Nesterov accelerated adam optimizer with an attention mechanism by Abeer Saber, Tamer Emara, Samar Elbedwehy, Esraa Hassan

“…However, advancements in digital technologies and computer vision have enabled convolutional neural networks (CNNs) to learn features automatically, thereby overcoming these challenges. …”
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Development and validation of machine learning models for osteoporosis prediction in chronic kidney disease patients: Data from National Health and Nutrition Examination survey by Hui Li, Ya Zhang, Chong Zhang

“…Model performance was evaluated using receiver operating characteristic curves, F1 scores, Matthews correlation coefficient, and Brier scores. …”
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A multimodal travel route recommendation system leveraging visual Transformers and self-attention mechanisms by Zhang Juan, Jing Zhang, Ming Gao

“…Concurrently, a Long Short-Term Memory (LSTM) network encodes sequential data to capture the temporal dependencies within travel sequences. …”
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Application of artificial intelligence for commodity identification for customs purposes by Galina Yu. Fedotova, Anna Yu. Komelova

“…As a model, the neural network of artificial intelligence developed by the World Customs Organization is used. …”
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UAP: A System Authentication Protocol for UAV Relay Communication by UAV-Assisted by Chunpeng Liu, Tao Huang, Maode Ma

“…The application scenarios and security features of UAP are also considered, making it a solution for UAV applications.…”
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Predicting the Event Types in the Human Brain: A Modeling Study Based on Embedding Vectors and Large-Scale Situation Type Datasets in Mandarin Chinese by Xiaorui Ma, Hongchao Liu

“…This work constructs datasets of considerable semantic complexity, comprising a substantial volume of verbs along with their feature vectors and situation type labels, which can be used for evaluating large language models in the future.…”
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Novel Federated Graph Contrastive Learning for IoMT Security: Protecting Data Poisoning and Inference Attacks by Amarudin Daulay, Kalamullah Ramli, Ruki Harwahyu, Taufik Hidayat, Bernardi Pranggono

“…We evaluate FedGCL on four benchmark malware datasets (Drebin, Malgenome, Kronodroid, and TUANDROMD) using 5 to 15 graph neural network clients over 20 communication rounds. …”
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Integrative spatial omics reveals distinct tumor-promoting multicellular niches and immunosuppressive mechanisms in Black American and White American patients with TNBC by Qian Zhu, Akhila Balasubramanian, Jaya Ruth Asirvatham, Megha Chatterjee, Badrajee Piyarathna, Jaspreet Kaur, Nada Mohamed, Ling Wu, Stacy Wang, Niloufar Pourfarrokh, Paula Danika Binsol, Mahak Bhargava, Uttam Rasaily, Yitian Xu, Junjun Zheng, Deborah Jebakumar, Arundhati Rao, Carolina Gutierrez, Angela R. Omilian, Carl Morrison, Gokul M. Das, Christine Ambrosone, Erin H. Seeley, Shu-hsia Chen, Yi Li, Eric Chang, Xiaoxian Li, Elizabeth Baker, Ritu Aneja, Xiang H.-F. Zhang, Arun Sreekumar

“…Ligand-receptor and pathway analyses further demonstrated that BA TNBC tumors exhibit a relatively “immune-cold” profile, while WA TNBC tumors display features of an “inflamed” TME, suggesting the evolution of a unique immunosuppressive mechanism. …”
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Use of Xception Architecture for the Classification of Skin Lesions by Cledmir Tejada, Gustavo Espinoza, Daniel Subauste

“…The Xception architecture, a deep convolutional neural network, serves as the foundational model, supplemented with customized classification layers for specialized features and predictions. …”
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Certificateless aggregate signcryption scheme with multi-ciphertext equality test for the internet of vehicles. by Xiaodong Yang, Xilai Luo, Ruixia Liu, Songyu Li, Ke Yao

“…The Internet of Vehicles (IoV) facilitates connectivity among vehicles, roadside units, and smart terminals, enabling the evolution of traditional traffic networks into intelligent transport systems. …”
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Fatigue Load Prediction of Wind Turbine Drive Train Based on CNN-BiLSTM by Xiaodong WANG, Qing LI, Deyi FU, Yingming LIU, Ruojin WANG

“…We propose a fatigue load prediction model for the drivetrain system based on a convolutional neural network-bidirectional long short-term memory (CNN-BiLSTM) architecture, utilizing state data from wind turbines. …”
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