Application Value of an AI-based Imaging Feature Parameter Model 
for Predicting the Malignancy of Part-solid Pulmonary Nodule by Mingzhi LIN, Yiming HUI, Bin LI, Peilin ZHAO, Zhizhong ZHENG, Zhuowen YANG, Zhipeng SU, Yuqi MENG, Tieniu SONG

“…All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. …”
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Discrimination Features by Wavelet Transformation by Faten Mustafa, Turkan Khalil, Almas Khalil

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Efficient Multi-Task Training with Adaptive Feature Alignment for Universal Image Segmentation by Yipeng Qu, Joohee Kim

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The Changes in Color and Image Parameters and Sensory Attributes of Freeze-Dried Clones and a Cultivar of Red-Fleshed Apples by Ewa Ropelewska, Mariusz Lewandowski

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Differentiating Emphysema From Emphysema-Dominated COPD Patients with CT Imaging Feature and Machine Learning by Guo W, Li M, Li Y, Fan X, Wu L

“…All participants underwent spirometry and chest CT scans. QCT features including emphysema index, mean lung density, airway measurements, and vessel measurements were extracted. …”
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THE AGE-RELATED FEATURES OF ALVEOLAR JAWS BONE MINERAL DENSITY IN GROWING CHILDREN by V.F. Makeev, A-S.A. Krupnyk

“…Not only jaw shape, linear dimensions and bone tissue amount can be determined by 3D method but biological parameters such as bone density. The aim of the present research was to study the age-related features of alveolar jaws bone mineral density in growing children using computer tomography. …”
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Quantitative comparison between single-photon emission computed tomography and positron emission tomography imaging of lung ventilation with 99mTc-technegas and 68Ga-gallgas in pat... by Enrique Gustavo Cuna, Juan Pablo Gambini, Liliana Servente, Eduardo Savio, Henry William Engler, Gabriel Adrián González, Omar Alonso

“…The aim of this study was quantitative comparison between 68Ga-Gallgas positron emission tomography (PET) and 99mTc-Technegas single photon emission computed tomography (SPECT) for lung ventilation function assessment in patients with moderate-to-severe obstructive pulmonary disease and to identify image-derived texture features correlating to the physiologic parameters. …”
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A KWS System for Edge-Computing Applications with Analog-Based Feature Extraction and Learned Step Size Quantized Classifier by Yukai Shen, Binyi Wu, Dietmar Straeussnigg, Eric Gutierrez

“…Edge-computing applications demand ultra-low-power architectures for both feature extraction and classification tasks. …”
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Effect of block geometry on the estimation of low volumetric block proportions: A tunneling-based computer bimrock model by Zixin Zhao, Guolong Zhu, Xingliang Peng, Fawu Wang

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A Flow Shop Scheduling Method Based on Dual BP Neural Networks with Multi-Layer Topology Feature Parameters by Hui Mu, Zinuo Wang, Jiaqi Chen, Guoqiang Zhang, Shaocun Wang, Fuqiang Zhang

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Similarity and wavelet transform based data partitioning and parameter learning for fuzzy neural network by Pramoda Patro, Krishna Kumar, G. Suresh Kumar, Gandharba Swain

“…Neurons weight and bias values are computed by adapting wavelet functions. Finally, parameters of the fuzzy neural networks are fine-tuned using the hybrid ant colony particle swarm optimization (HASO). …”
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Pulmonary diseases accurate recognition using adaptive multiscale feature fusion in chest radiography by Mengran Zhou, Lipeng Gao, Kai Bian, Haonan Wang, Ning Wang, Yue Chen, Siyi Liu

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Feature Selection Using a Genetic Algorithms and Fuzzy logic in Anti-Human Immunodeficiency Virus Prediction for Drug Discovery by Houda Labjar, Mohammad Al-Sarem, Mohamed Kissi

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Multi-scale feature fusion and feature calibration with edge information enhancement for remote sensing object detection by Lihua Yang, Yi Gu, Hao Feng

“…Abstract Vision Transformer-based detectors have achieved remarkable success in the field of object detection, but the application of these models to high-resolution remote sensing imagery faces challenges in computational costs and performance bottlenecks due to the increased computational complexity required to process high-resolution imagery, especially when capturing fine-grained edge features. …”
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MapSAM: adapting segment anything model for automated feature detection in historical maps by Xue Xia, Daiwei Zhang, Wenxuan Song, Wei Huang, Lorenz Hurni

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Using Permutation-Based Feature Importance for Improved Machine Learning Model Performance at Reduced Costs by Adam Khan, Asad Ali, Jahangir Khan, Fasee Ullah, Muhammad Faheem

“…These selected features were used to retrain the ML models without hyperparameters (default settings) to determine whether similar performance could be achieved at low computational cost. …”
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SFG-YOLOv8: efficient and lightweight small-feature gesture keypoint detector by Weimin Che, Hui Zhang, Bangxue Wu, Qun Li, Hongji Zhang, Shilong Yuan, Hongcheng Yang

“…This paper introduces SFG-YOLOv8, an efficient and lightweight gesture keypoint detector designed for low-computational-power AR scenarios. We propose SFG-ShuffleNetV2 as the backbone network by improving the convolution operation, resulting in fewer parameters, and introduce the contextual bottleneck refinement module (CBRM) to enlarge the receptive field, enhancing the capture of the global context. …”
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DOA Estimation by Feature Extraction Based on Parallel Deep Neural Networks and MRMR Feature Selection Algorithm by Ashwaq Neaman Hassan Al-Tameemi, Mahmood Mohassel Feghhi, Behzad Mozaffari Tazehkand

“…The results by computer simulations on a uniform linear array show that the proposed structure significantly increases the accuracy of DOA estimation and is more robust to changes in input parameters than traditional algorithms, such as estimation of signal parameters via invariant rotation (ESPRIT), classification of multiple signals (MUSIC), and DNN method. …”
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Research on Adaptive Discriminating Method of Brain–Computer Interface for Motor Imagination by Jifeng Gong, Huitong Liu, Fang Duan, Yan Che, Zheng Yan

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Features of simple inflammation markers in assessing the plaque vulnerability in patients with acute coronary syndrome by A. N. Kovalskaya, G. R. Bikbaeva, D. V. Duplyakov, E. V. Savinova

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