Discretization-independent surrogate modeling of physical fields around variable geometries using coordinate-based networks by James Duvall, Karthik Duraisamy

“…Surrogate modeling techniques aim to decrease computational expense while retaining dominant solution features and characteristics. Existing frameworks based on convolutional neural networks and snapshot-matrix decomposition often rely on lossy pixelization and data-preprocessing, limiting their effectiveness in realistic engineering scenarios. …”
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Optimizing learning outcomes: a deep dive into hybrid AI models for adaptive educational feedback by Hafiz Muhammad Qadir, M. Taseer Suleman, Rafaqat Alam Khan, Muhammad Sohaib, Md Junayed Hasan, Syed Abid Hussain

“…Abstract Accurate prediction of student performance is essential for the creation of adaptive learning frameworks and the best utilization of educational strategies. …”
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Research on the Automatic Multi-Label Classification of Flight Instructor Comments Based on Transformer and Graph Neural Networks by Zejian Liang, Yunxiang Zhao, Mengyuan Wang, Hong Huang, Haiwen Xu

“…Traditional written evaluations conducted by flight instructors are often marred by subjectivity and inefficiency, rendering them inadequate to satisfy the stringent demands of Competency-Based Training and Assessment (CBTA) frameworks. To address this challenge, this study presents a novel multi-label classification model that seamlessly integrates RoBERTa, a robust language model, with Graph Convolutional Networks (GCNs). …”
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Study of line spectra emitted by hydrogen isotopes in tokamaks through Deep-Learning algorithms by N. Saura, M. Koubiti, S. Benkadda

“…The paper focuses on the application of the convolutional neural network (CNN) algorithm to emission spectroscopy from the divertor regions of magnetic fusion devices. …”
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Scalable and Efficient Multi-Class Brain Tumor Classification with a Compact Hybrid Deep Learning Model for Real-Time Applications by Sohaib R. Awad, Amar I. Daood, Akram A. Dawood

“…A new hybrid deep learning solution merges convolutional neural networks (CNNs) with support vector machines (SVMs) to improve classification results as this paper describes. …”
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Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations by Phuc Hao do, Tran Duc Le, Truong Duy Dinh, van Dai Pham

“…The integration of KAN-based models into existing cybersecurity frameworks can enhance the detection and mitigation of sophisticated botnet threats, thus contributing to more resilient and secure IoT ecosystems.…”
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Advancements in artificial intelligence and machine learning for poultry farming: Applications, challenges, and future prospects by Muhammad Halim Natsir, Wayan Firdaus Mahmudy, Mochamad Tono, Yuli Frita Nuningtyas

“…Future directions include developing lightweight, energy-efficient models, enhancing user-friendly interfaces, and promoting policy frameworks that support ethical and inclusive AI adoption. …”
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Research on graph-based heterogeneous data integration method by HUANG Yuezhen, YANG Fen, TIAN Feng, ZHANG Chengye, LI Yuchan

“…Through verification on real data within the enterprise, the experimental results show that the framework proposed in the paper can improve the development efficiency of data integration, and the model is not limited by business fields and has strong portability.…”
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Enhancing Privacy by Large Mask Inpainting and Fusion-Based Segmentation in Street View Imagery by Mahdi Khourishandiz, Abdollah Amirkhani

“…To address this, we propose a novel framework that automatically detects and removes sensitive objects, such as pedestrians and vehicles, ensuring robust privacy preservation while maintaining the visual integrity of the images. …”
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Research on graph-based heterogeneous data integration method by HUANG Yuezhen, YANG Fen, TIAN Feng, ZHANG Chengye, LI Yuchan

“…Through verification on real data within the enterprise, the experimental results show that the framework proposed in the paper can improve the development efficiency of data integration, and the model is not limited by business fields and has strong portability.…”
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NeuroTIS+: An Improved Method for Translation Initiation Site Prediction in Full-Length mRNA Sequence via Primary Structural Information by Wenqiu Xiao, Chao Wei

“…In this paper, under the framework of NeuroTIS, we propose its enhanced version, NeuroTIS+, which allows for more sophisticated codon label dependency modeling via temporal convolution and homogenous feature building through an adaptive grouping strategy. …”
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Incremental Cotton Diseases Detection Based on Aerial Remote Sensing Image and Blockchain Sharding by Jing Nie, Haochen Li, Yang Li, Jingbin Li, Xuewei Chao, Sezai Ercisli

“…The UAV-IFOD- shard framework improves the system throughput of federated learning and the quality of the aggregated model, and also shows better performance in the face of malicious node attacks, and it is a good choice to use this framework for cotton pest and disease detection in Xinjiang.…”
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WEDM: Wavelet-Enhanced Diffusion with Multi-Stage Frequency Learning for Underwater Image Enhancement by Junhao Chen, Sichao Ye, Xiong Ouyang, Jiayan Zhuang

“…In this paper, we propose a novel UIE framework, the Wavelet-based Enhancement Diffusion Model (WEDM), which integrates frequency-domain decomposition with diffusion models. …”
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Face Anti-Spoofing Based on Adaptive Channel Enhancement and Intra-Class Constraint by Ye Li, Wenzhe Sun, Zuhe Li, Xiang Guo

“…To address these issues, we propose a jointly optimized framework integrating the Enhanced Channel Attention (ECA) mechanism and the Intra-Class Differentiator (ICD). …”
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Joint neural denoising and consolidation for portable handheld laser scan by T. Zhang, S. Filin

“…We argue that if treated jointly, richer shape context features can be learned and an improved enhancement framework can be derived. Accordingly, we formulate the shape context description as a joint contribution by both denoising and consolidation, within an end-to-end framework. …”
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Spintronic Memtransistor Leaky Integrate and Fire Neuron for Spiking Neural Networks by Aijaz H. Lone, Meng Tang, Daniel N. Rahimi, Xuecui Zou, Dongxing Zheng, Hossein Fariborzi, Xixiang Zhang, Gianluca Setti

“…When integrated into SNN and convolutional SNN frameworks, the device achieves classification precision above 96%. …”
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Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review by José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, Eduardo Maio, Eduardo Maio, Eduardo Maio, Pedro Afonso, Pedro Afonso, Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, Guilherme F. Machado, Guilherme F. Machado, Ryland Morgans, Tiago M. Barbosa, Tiago M. Barbosa, António M. Monteiro, António M. Monteiro, Pedro Forte, Pedro Forte, Pedro Forte, Ricardo Ferraz, Ricardo Ferraz, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho

“…A total of 2,548 articles were identified following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and the Population-Intervention-Comparators-Outcomes framework. By synthesizing findings from 32 studies, this review elucidates the available AI-based techniques to analyze tactical behavior and identify the collective dynamic based on artificial neural networks, deep learning, machine learning, and time-series techniques. …”
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“Locality – Adaptation” Research of Hydropower Resettlement Communities in the Jinsha River Basin: A Case Study of Ludila Hydropower Station by Fang WANG, Zhuoqi LI, Haoyi XU, Jiaqi YAN

“…At the settlement scale, the Mask Region-based Convolutional Neural Network (Mask R-CNN) deep learning model is utilized to identify architectural spatial features, categorizing three typical building types: traditional pitched-roof buildings, uniformly planned flat-roof buildings, and color steel plate-modified structures. …”
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Rice Leaf Disease Image Enhancement Based on Improved CycleGAN by YAN Congkuan, ZHU Dequan, MENG Fankai, YANG Yuqing, TANG Qixing, ZHANG Aifang, LIAO Juan

“…To address these challenges, a data augmentation method for rice leaf disease images was proposed based on an improved CycleGAN model in this reseach which aimed to expand disease image datasets by generating disease features, thereby alleviating the burden of collecting real disease data and providing more comprehensive and diverse data to support automatic rice disease recognition.MethodsThe proposed approach built upon the CycleGAN framework, with a key modification being the integration of a convolutional block attention module (CBAM) into the generator's residual module. …”
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Hyperdimensional Intelligent Sensing for Efficient Real-Time Audio Processing on Extreme Edge by Sanggeon Yun, Ryozo Masukawa, Hanning Chen, Sungheon Jeong, Wenjun Huang, Arghavan Rezvani, Minhyoung Na, Yoshiki Yamaguchi, Mohsen Imani

“…This paper proposes a groundbreaking approach with a near-sensor model tailored for intelligent audio-sensing frameworks. Utilizing a Fast Fourier Transform (FFT) module, convolutional neural network (CNN) layers, and HyperDimensional Computing (HDC), our model excels in low-energy, rapid inference, and online learning. …”
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