Explainable AI for Bipolar Disorder Diagnosis Using Hjorth Parameters by Mehrnaz Saghab Torbati, Ahmad Zandbagleh, Mohammad Reza Daliri, Amirmasoud Ahmadi, Reza Rostami, Reza Kazemi

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LV-FeatEx: Large Viewpoint-Image Feature Extraction by Yukai Wang, Yinghui Wang, Wenzhuo Li, Yanxing Liang, Liangyi Huang, Xiaojuan Ning

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Formation of Machine Learning Features Based on the Construction of Tropical Functions by Sergey N. Chukanov, Ilya S. Chukanov

“…To increase the variety of parameters (machine learning features), filtering of object scanning by rows from left to right and scanning by columns from bottom to top are built. …”
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Co-occurrence feature learning for visual recognition of immature leukocytes by Yi-Ting Hsiao, Si-Wa Chan, Yen-Chieh Ouyang, Ju-Huei Chien

“…Manual examination of blood smear images for leukemia diagnosis is often laborious and costly. Computer-aided classification of WBCs has the potential to assist hematologists in improving diagnostic accuracy. …”
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Cross-Architecture Vulnerability Detection Combining Semantic and Attribute Feature by LI Kun, LI Bin, ZHU Wenjing, ZHOU Qinglei

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Boosted-SpringDTW for Comprehensive Feature Extraction of PPG Signals by Jonathan Martinez, Kaan Sel, Bobak J. Mortazavi, Roozbeh Jafari

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Facial Expression Recognition Algorithm Combining Parallel Network Features by MIAO Zhuang, CHENG Wei-yue, LIN Ke-zheng, LI Ao

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Virtual Reality Video Image Classification Based on Texture Features by Guofang Qin, Guoliang Qin

“…Finally, based on DenseNet, an improved shallow layer dense convolutional neural network (L-DenseNet) is proposed, which can compress network parameters and improve the feature extraction ability of the network. …”
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MatSwarm: trusted swarm transfer learning driven materials computation for secure big data sharing by Ran Wang, Cheng Xu, Shuhao Zhang, Fangwen Ye, Yusen Tang, Sisui Tang, Hangning Zhang, Wendi Du, Xiaotong Zhang

“…MatSwarm features two key innovations: a swarm transfer learning method with a regularization term to enhance the alignment of local model parameters, and the use of Trusted Execution Environments (TEE) with Intel SGX for heightened security. …”
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Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images by Taojuan Li, Wen Liu, Mingxian Song, Zheng Gu, Ling Hai

“…First, we introduce an efficient multiscale convolutional (EMSC) module to improve feature extraction from complex backgrounds and enhance multiscale representation. …”
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Fusion of Deep and Time–Frequency Local Features for Melanoma Skin Cancer Detection by Hamidreza Eghtesaddoust, Morteza Valizadeh, Mehdi Chehel Amirani

“…The scale-invariant feature transform (SIFT) descriptors are handcrafted local features computed from the four subbands of one-level two-dimensional discrete wavelet transform (2D DWT). …”
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Feasibility study of AI-assisted multi-parameter MRI diagnosis of prostate cancer by Yibo Xu, Rongjiang Wang, Zhihai Fang, Jianer Tang

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Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli. by Tristan Aumentado-Armstrong, Michael G Metzen, Michael K J Sproule, Maurice J Chacron

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THE USE OF COMPUTATIONAL SIMULATION TO INCREASE THE EFFICIENCY OF ACTIONS TO REDUCE THE LOSS OF ELECTRIC POWER by A. Grin, I. Skorokhodova, C. Chebanov, A. Grin

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Computational modelling reveals neurobiological contributions to static and dynamic functional connectivity patterns by Linnea Hoheisel, Linnea Hoheisel, Hannah Hacker, Gereon R Fink, Gereon R Fink, Silvia Daun, Silvia Daun, Joseph Kambeitz, Joseph Kambeitz

“…We analysed associations between brain-wide sFC and TC features with optimal model parameters and fits with a univariate correlation approach and multivariate prediction models. …”
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A multiobjective continuation method to compute the regularization path of deep neural networks by Augustina Chidinma Amakor, Konstantin Sonntag, Sebastian Peitz

“…However, due to the non-smoothness of the ℓ1 norm and the large number of parameters, this approach is not very efficient from a computational perspective. …”
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Study of kinetic performance effect on wheel and rail wear using computer simulation by Lev I. Evelson, Evgeny A. Pamfilov, Alexander G. Tsygankov, Ludmila I. Shiryaeva

“…The study object is a “wheel - rail” system. The subject is the computer simulation of the system elements wear. The work objective is to investigate the wheel and rail wear dependence on the kinetic performance parameters. …”
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Statistical Analysis of Local Extrema in Rough Sea Surfaces Based on Computer Simulation by N. S. Pyko, E. D. Orandarenko, M. I. Bogachev

“…Analysis of the functional forms governing the local extreme value distributions in a rough sea surface for the given wind and swell parameters based on computer simulations.   Materials and methods. …”
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A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data by Ovais A Jaffery, Lea Melki, Gregory Slabaugh, Wilson W Good, Caroline H Roney

“…However, the optimal methods that can potentially constitute a clinically relevant in silico treatment are still being investigated and face limitations, such as uncertainty of electroanatomical data recordings, generation and calibration of models within clinical timelines and requirements to validate or benchmark the recovered tissue parameters. This paper is aimed at reporting techniques on the personalisation of cardiac computational models, with a focus on calibrating cardiac tissue conductivity based on electroanatomical mapping data.…”
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Refined Judgment of Urban Traffic State Based on Machine Learning and Edge Computing by Lijuan Liu

“…This paper aims to study the recognition of urban traffic conditions and refine the recognition through the improvement of edge computing algorithms. This paper proposes a method to calculate traffic flow parameters, preprocess the traffic flow data, delete irrelevant features, use flow theory to delete wrong data, and change the data in time according to actual needs, carrying out refined discrimination and analysis of urban traffic status. …”
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