Efficient compression of encoder-decoder models for semantic segmentation using the separation index by Movahed Jamshidi, Ahmad Kalhor, Abdol-Hossein Vahabie

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Improved lightweight DeepLabV3+ for bare rock extraction from high-resolution UAV imagery by Pengde Lai, Chao Lv, Lv Zhou, Shengxiong Yang, Jiao Xu, Qiulin Dong, Meilin He

“…Meanwhile, the improved model had a parameter count of 6.98 M and a computational complexity of 7.24G, achieving enhanced accuracy while maintaining computational efficiency. …”
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Automated mechanical ventilator design and analysis using neural network by S. Hariharan, Hemalatha Karnan, D. Uma Maheswari

“…The handling of mechanical ventilators is to be done under the assistance of trained professionals and demands the selection of ideal parameters. In this work, a computer-aided simulation of ventilator design is performed for clinical complications like pneumonia and Chronic Obstructive Pulmonary Disease (COPD) and is validated against normal ventilatory parameters. …”
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DCE-YOLOv8: Lightweight and Accurate Object Detection for Drone Vision by Jinsu An, Dong Hee Lee, Muhamad Dwisnanto Putro, Byeong Woo Kim

“…The ERB(Efficient Residual Bottleneck) and DCE(Divided Context Extraction) modules are incorporated into the Backbone, with the ERB module reducing the number of parameters to render the model more lightweight. The DCE module focuses on extracting features pertinent to small objects. …”
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A hybrid theoretical–numerical–experimental framework for robust health monitoring of thin-walled hollow composite members using guided waves by Akshay Prakash Kalgutkar, Shirsendu Sikdar, Sauvik Banerjee, Karl Walton, Rakesh Mishra

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TTPRNet: A Real-Time and Precise Tea Tree Pest Recognition Model in Complex Tea Garden Environments by Yane Li, Ting Chen, Fang Xia, Hailin Feng, Yaoping Ruan, Xiang Weng, Xiaoxing Weng

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Comparative analysis of the ten Tusscher and Tomek human ventricular cell models at cellular, tissue, and organ levels: Implications for post‐infarct ventricular tachycardia simula... by Ruiqing Dong, Zhenyin Fu, Chuxin Zhang, Yumeng Liu, Yiming Wang, Nan Zhang, Zefeng Wang, Jun Hou, Ling Xia, Yongquan Wu, Shijie Zhou, Dongdong Deng

“…Abstract Computational modeling is a tool for exploring both normal electrical propagation in healthy hearts and cardiac arrhythmias in patients. …”
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Enabling Predication of the Deep Learning Algorithms for Low-Dose CT Scan Image Denoising Models: A Systematic Literature Review by Muhammad Zubair, Helmi B. Md Rais, Fasee Ullah, Qasem Al-Tashi, Muhammad Faheem, Arfat Ahmad Khan

“…These drawbacks significantly reduce the diagnostic capabilities of Computer-Aided Diagnosis (CAD) systems. Eliminating these noises and artifacts while preserving critical features poses a significant challenge. …”
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Towards Precise Papaya Ripeness Assessment: A Deep Learning Framework with Dynamic Detection Heads by Haohai You, Jing Fan, Dongyan Huang, Weilong Yan, Xiting Zhang, Zhenke Sun, Hongtao Liu, Jun Yuan

“…First, the width factor of YOLOv8n is adjusted to construct a lightweight backbone network, YOLO-Ting. Second, a low-computation ADown module is introduced to replace the standard downsampling structure, aiming to enhance feature extraction efficiency. …”
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Instantaneous Metabolic Energetics: Data-Driven Modeling Using Function-Based Surrogates and Gradient Boosting by Christopher Buglino, William Z. Peng, Stacy Ashlyn, Hyunjong Song, Howard J. Hillstrom, Joo H. Kim

“…Results: The model accurately predicts instantaneous MEE without subject-specific input parameters. Shapley Additive Explanations were used to investigate energetic features of the learned MEE function and demonstrate alignment with literature. …”
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Unlocking the potential of secure communications: A comprehensive systematic review of the network design model for topology control and routing synergy in wireless sensor networks... by Taher Alzahrani, Saima Rashid

“…Dynamics are implemented for researching the behavior of network topologies in delayed parameters. The center manifold theorem applies to figure out the features of expanding recurring fluctuations. …”
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Assimilating Satellite-Based Biophysical Variables Data into AquaCrop Model for Silage Maize Yield Estimation Using Water Cycle Algorithm by Elahe Akbari, Ali Darvishi Boloorani, Jochem Verrelst, Stefano Pignatti

“…In this paper, the AquaCrop model, a water-driven crop growth model, was selected for recalibration and assimilation of satellite-derived biophysical products due to its simplicity and lack of computational complexity. To this end, field samples of soil (sampled before cultivation) and crop features were collected during the growing season of silage maize. …”
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Prevalence, Geometry, and Hemodynamics of Small and Medium-Sized Intracranial Aneurysms With and Without Blebs in the Chinese Han Population by Xiaopeng Cui, Yan Zhao, Liang Wang, Yujing Jin, Zhenglong Yang, Yaohua Li, Zilin Zhao, Hengrui Zhang, Kai Wei, Zhennan Sun, Peng Huai, Lei Chen, Xinyu Yang

“…Objectives To investigate the prevalence, distribution, and associated clinical, geometric, and hemodynamic features of blebs in small- and medium-sized IAs among Chinese patients, and to identify predictors of aneurysm rupture and bleb formation. …”
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Population dynamics and monitoring applied to decision-making by M. J. Conroy, D. C. Lee

“…Finally, calibration of model parameters is obtained by comparing predicted with observed abundance. …”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…In its optimal configuration, the EcoTaskSched model is successfully applied to fog-cloud computing environments, increasing task handling efficiency and reducing energy consumption while maintaining the required QoS parameters. …”
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Radiomics approach for identifying radiation-induced normal tissue toxicity in the lung by Olivia G. G. Drayson, Pierre Montay-Gruel, Charles L. Limoli

“…Abstract The rapidly evolving field of radiomics has shown that radiomic features are able to capture characteristics of both tumor and normal tissue that can be used to make accurate and clinically relevant predictions. …”
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An Easily Scalable Docker-Based Privacy-Preserving Malicious Traffic Detection Architecture for IoT Environments by Tong Niu, Yaqiu Liu, Qingfeng Li, Qichi Bao

“…The payload of the data packets is encoded to enhance the feature extraction capability of the model. The model is then trained using federated learning/edge computing to ensure data privacy. …”
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Visual Automatic Localization Method Based on Multi-level Video Transformer by Qiping ZOU, Botao LI, Saian CHEN, Xi GUO, Taohong ZHANG

“…At the core of the MLE are its dual attention modules: the Level-wise Learnable Attention (LWLA) and the Multi-level Cross Attention (MLCA), each stacked multiple times to deepen learning and integrate features more effectively. The LWLA employs a deformable attention mechanism, an innovative replacement for global attention that calculates feature similarity more flexibly and efficiently, reducing computational costs and mitigating slow convergence issues commonly associated with traditional models.　…”
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AUHF-DETR: A Lightweight Transformer with Spatial Attention and Wavelet Convolution for Embedded UAV Small Object Detection by Hengyu Guo, Qunyong Wu, Yuhang Wang

“…In the backbone, we introduce a novel WTC-AdaResNet paradigm that utilizes reversible connections to decouple small-object features. We further replace the original global attention mechanism with the PSA module to strengthen inter-feature relationships within each ROI, thereby resolving the embedded challenges posed by RT-DETR’s complex token computations. …”
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A Procedure for Developing a Flight Mechanics Model of a Three-Surface Drone Using Semi-Empirical Methods by Stefano Cacciola, Laura Testa, Matteo Saponi

“…The reference UAV chosen to test the proposed procedure is the Dragonfly DS-1, an electric VTOL UAV developed by Overspace Aviation, featuring a three-surface configuration. The accuracy of the polar data, i.e., the lift and drag coefficients, is assessed through comparisons with computational fluid dynamics simulations and flight data. …”
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