Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm by HE Yong jun, ZHANG Xue yuan, SHAO Hui li, DING Bo

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Prediction of Right Heart Failure in LVAD Candidates: Current Approaches and Future Directions by Frederick Vogel, Zachary W. Sollie, Arman Kilic, Ethan Kung

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An Analytical Framework for Risk Evaluation and Design of Infiltration Basins for Managed Aquifer Recharge by Aldo Fiori, Felipe P. J. de Barros, Alberto Bellin

“…Although the framework relies on simplifying assumptions, it provides a computationally efficient manner to obtain physical insights and relate model input parameters to decision making.…”
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Variability of morphometric traits of seeds of different genotypes of Lycium spp. by M. Yu. Zhurba, S. V. Klymenko, Iwona Szot

“…The analysis of coefficient of variation showed the difference of variability in morphometric characteristics between some Lycium spp. cultivars and varieties. The most variable features: seeds weight (8.51–28.22%) and seeds length (5.07–24.81%) are important parameters for selection. …”
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PHRF-RTDETR: a lightweight weed detection method for upland rice based on RT-DETR by Xianjin Jin, Jinheng Zhang, Fei Wang, Mengyan Zhao, Yunshuang Wang, Jianping Yang, Jinfeng Wu, Bing Zhou

“…Second, we integrate HiLo, a mechanism excluding parameter growth, into the AIFI module to enhance the model’s capability of capturing multi-frequency features. …”
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Abnormal gait recognition with millimetre‐wave radar based on perceptual loss and convolutional temporal autoencoder by Peng Zhao, Ling Hong, Yu Wang

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A Chinese Few-Shot Named-Entity Recognition Model Based on Multi-Label Prompts and Boundary Information by Cong Zhou, Baohua Huang, Yunjie Ling

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A Dynamic Inverse Decoupling Control Method for Reducing Energy Consumption in a Quadcopter UAV by Guoxin Ma, Kang Tian, Hongbo Sun, Yongyan Wang, Haitao Li

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Optimizing Artificial Neural Networks Using Mountain Gazelle Optimizer by Muhammed Abdulhamid Karabiyik, Bahaeddin Turkoglu, Tunc Asuroglu

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Self-supervision advances morphological profiling by unlocking powerful image representations by Vladislav Kim, Nikolaos Adaloglou, Marc Osterland, Flavio M. Morelli, Marah Halawa, Tim König, David Gnutt, Paula A. Marin Zapata

“…However, traditional feature extraction tools such as CellProfiler are computationally intensive and require frequent parameter adjustments. …”
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Learning the factors controlling mineral dissolution in three-dimensional fracture networks: applications in geologic carbon sequestration by Aleksandra A. Pachalieva, Aleksandra A. Pachalieva, Jeffrey D. Hyman, Daniel O’Malley, Gowri Srinivasan, Hari Viswanathan

“…This study is a first step towards characterizing the parameters that control carbon mineralization using an approach with integrates computational physics and machine learning.…”
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Quantitative Analysis of Conjunctival and Retinal Vessels in Fabry Disease by Andrea Sodi, Chiara Lenzetti, Daniela Bacherini, Lucia Finocchio, Tommaso Verdina, Isabella Borg, Francesca Cipollini, Fatema Ullah Patwary, Ilaria Tanini, Claudia Zoppetti, Stanislao Rizzo, Gianni Virgili

“…It has been described an increasing in retinal and conjunctival vessel tortuosity and this feature represents an important marker for the disease. …”
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TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Firstly, the Bottleneck convolution kernel channels in the C3 module were grouped to greatly reduce the number of parameters. Secondly, the C3 module in the neck is replaced by the Res2Net module, which extracts features at different scales through multiple branches, not only ensuring rich details, but also enhancing the generalization ability of the network. …”
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Attention-Based Multi-Learning Approach for Speech Emotion Recognition With Dilated Convolution by Samuel, Kakuba, Alwin, Poulose

“…The proposed ABMD model achieves comparable performance while taking global contextualized long-term dependencies between features in a parallel manner using a large receptive field with less increase in the number of parameters compared to the number of layers and considers spatial cues among the speech features. …”
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AUTOMATION OF OPTIMAL IDENTIFICATION OF DYNAMIC ELEMENT TRANSFER FUNCTIONS IN COMPLEX TECHNICAL OBJECTS BASED ON ACCELERATION CURVES by A. Yu. Alikov, M. A. Kovaleva, A. L. Rutkovskiy, N. V. Tedeeva

“…The aim of present paper is to minimise the errors in the approximation of experimentally obtained acceleration curves.Methods. Based on the features and disadvantages of the well-known Simoyu method for calculating transfer functions on the basis of acceleration curves, a modified version of the method is developed using the MathLab and MathCad software. …”
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An MCMC Approach to Bayesian Image Analysis in Fourier Space by Konstantinos Bakas, John Kornak, Hernando Ombao

“…Bayesian image analysis methods are commonly applied to solve image analysis problems such as noise reduction, feature enhancement, and object detection. A primary limitation of these methods is their computational cost due to the complex joint interdependencies between pixels, which limits the efficiency of performing posterior sampling through Markov chain Monte Carlo (MCMC). …”
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A lightweight UAV target detection algorithm based on improved YOLOv8s model by Fubao Ma, Ran Zhang, Bowen Zhu, Xirui Yang

“…Extensive experiments on the VisDrone2019 dataset show that the proposed model reduces parameters by 37.9 $$\%$$ , computational cost by 22.8 $$\%$$ , and model size by 36.9 $$\%$$ , while improving AP, AP50, and AP75 by 0.2 $$\%$$ , 0.2 $$\%$$ , and 0.4 $$\%$$ , respectively. …”
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Laser_RobMap: An open source ROS2 compatible tool for 3D mapping using a Mobile Robot and 2D LiDAR by Daniel D. Yanyachi, Yamir H. Anco-Agüero, German A. Echaiz, Miguel A. Esquivel, Alfredo Mamani-Saico, Pablo R. Yanyachi

“…The tool adapts to any ROS2-enabled robot that provides inertial and odometry data, with configurable parameters to optimize performance on systems with limited computational resources. …”
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Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches by Nafiseh Hosseini, Hamid Tanzadehpanah, Amin Mansoori, Mostafa Sabzekar, Gordon A. Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

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A Novel Approach for Tomato Leaf Disease Classification with Deep Convolutional Neural Networks by Gizem Irmak, Ahmet Saygılı

“…Computer-aided automation systems for the detection of plant diseases represent a challenging and highly impactful research domain in the field of agriculture. …”
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