A brain tumor segmentation method based on attention mechanism by Juan Cao, Jinjia Liu, Jiaran Chen

“…BSAU-Net incorporates an edge feature extraction module (EA) based on the Sobel operator, enhancing the model’s sensitivity to tumor regions while preserving edge contours. …”
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Luminaire Detection through Brightness Enhanced Mask R-CNN in Tunnel Environment by B. Xu, L. Liu, L. Liu, X. Qin, X. Qin, L. Xie, L. Xie

“…Leveraging tunnel gray-scale images and the Mask R-CNN object detection framework, a feature fusion network based on ResNet-FPN, trained via transfer learning, which enhances performance in detecting object luminaires. …”
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Enhanced mask R-CNN for luminaire detection through brightness balancing and distribution-guided optimization in tunnels by Xiaoqiong Qin, Bintao Xu, Chenchen Wang, Lirui Liu, Linfu Xie, Rong Liu, Mingwei Hu, Xiangsheng Chen

“…Leveraging tunnel gray-scale images and the Mask R-CNN object detection framework, a feature fusion network based on ResNet-FPN, trained via transfer learning, which enhances performance in detecting object luminaires. …”
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Prediction of copper contamination in soil across EU using spectroscopy and machine learning: Handling class imbalance problem by Chongchong Qi, Nana Zhou, Tao Hu, Mengting Wu, Qiusong Chen, Han Wang, Kejing Zhang, Zhang Lin

“…Hyperparameter optimization was applied to enhance model performance, and multiple statistical metrics were employed for evaluation. …”
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The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…The data are cleaned, standardized, and feature-engineered to meet the input requirements of neural network models. …”
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Application of Elastic networks and Bayesian networks to explore influencing factors associated with arthritis in middle-aged and older adults in the Chinese community by Tao Zhong, Tianlun Li, Jiapei Hu, Jiayi Hu, Li Jin, Yuxuan Xie, Bin Ma, Bin Ma, Dailun Hu

“…First, Elastic networks (ENs) were used to screen for features closely associated with arthritis, and we subsequently incorporated these features into the construction of the BNs model. …”
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Predicting outcomes following open abdominal aortic aneurysm repair using machine learning by Ben Li, Badr Aljabri, Derek Beaton, Leen Al-Omran, Mohamad A. Hussain, Douglas S. Lee, Duminda N. Wijeysundera, Ori D. Rotstein, Charles de Mestral, Muhammad Mamdani, Mohammed Al-Omran

“…Using 10-fold cross-validation, 6 ML models were trained using pre-operative features with logistic regression as the baseline comparator. …”
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An efficient patient’s response predicting system using multi-scale dilated ensemble network framework with optimization strategy by Nalini Manogaran, Nirupama Panabakam, Durai Selvaraj, Koteeswaran Seerangan, Firoz Khan, Shitharth Selvarajan

“…The selected weight features are input into the prediction process. Here, the prediction is performed by Multi-scale Dilated Ensemble Network (MDEN), where we integrated Long-Short term Memory (LSTM), Recurrent Neural Network (RNN) and One-dimensional Convolutional Neural Networks (1DCNN). …”
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Design of a Drivable Area Segmentation Network Using a Field Programmable Gate Array Based on Light Detection and Ranging by Xue-Qian Lin, Jyun-Yu Jhang, Cheng-Jian Lin, Sheng-Fu Liang

“…The proposed DASNet utilizes depthwise separable convolution as a basis/platform for feature extraction to enable features to be efficiently extracted to reduce both the computational load and required network parameters. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli, Rani Kumari, Adnan Akhunzada, Korhan Cengiz, Santosh Kumar Sharma, Rakesh Ranjan Kumar, Dinesh Kumar Sah

“…For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”
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Type recognition and parameter identification of power quality disturbances using improved 1D-YOLO and multi-task learning by Luo Bin, Wang Huifang, Ma Yongji, Chen Wentong, Li Yiming, Ni Xuming

“…The proposed model utilizes a Path Aggregation Network (PANet) for advanced multi-scale feature fusion, while decoupled heads enable concurrent analysis of 10 PQD elements. …”
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An integrated simulation framework for system-of-systems value exploration by Carl Nils Konrad Toller Melén, Raj Jiten Machchhar, Cecilia Wendin, Marco Bertoni

“…Especially when dealing with a system-of-systems (SoS), evaluating performance across diverse contexts and business models while understanding the interconnectedness between systems becomes critical. …”
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Joint Class and Domain Continual Learning for Decentralized Federated Processes by Chiara Lanza, Tinne Tuytelaars, Marco Miozzo, Eduard Angelats, Paolo Dini

“…Thanks to KD, the learning process can be performed without any prior information about the model architecture, i.e., every local model can be based on different architectures, which can also differ from the global. …”
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Seeing Beyond Noise: Improving Cryptocurrency Forecasting with Linear Bias Correction by Sibtain Syed, Syed Muhammad Talha, Arshad Iqbal, Naveed Ahmad, Mohammed Ali Alshara

“…The proposed methodology includes collecting cryptocurrency data and precious metal data from Coindesk and BullionVault, respectively, and then finding the optimal model input combination for each cryptocurrency by lag adjustment and correlating feature selection. …”
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Association of Pelvic Organ Prolapse and Changes in Bone Imaging Biomarkers in Postmenopausal Women with Low Bone Mineral Density by María Pérez Arguedas, Ernesto Bas Esteve, Alenda Jiménez García, Francisco Nohales Alfonso, Ana Jimenez-Pastor, Luis Martí-Bonmatí

“…An X-ray of the spine was performed followed by a computational image analysis to quantify textural features on each vertebral body. …”
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DNA methylation remodeling in temozolomide resistant recurrent glioblastoma: comparing epigenetic dynamics in vitro and in vivo by Michela Buonaiuto, Mariella Cuomo, Davide Costabile, Federica Trio, Sara Ferraro, Ornella Affinito, Alberto De Bellis, Maria Laura Del Basso De Caro, Roberta Visconti, Lorenzo Chiariotti, Giuseppe Catapano, Rosa Della Monica

“…Therefore, we generated a TMZ-resistant cell model and studied the epigenetic features acquired after selective temozolomide pressure. …”
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Risk Factors and Comorbidities Associated to Cardiovascular Disease in Qatar: A Machine Learning Based Case-Control Study by Hamada R. H. Al-Absi, Mahmoud Ahmed Refaee, Atiq Ur Rehman, Mohammad Tariqul Islam, Samir Brahim Belhaouari, Tanvir Alam

“…Moreover, the inclusion of the proposed novel factors into the ML model provides better performance than the model with traditional known risk factors for CVD. …”
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Quantitative Structure Activity Relationship Studies of Topoisomerase I Inhibitors as Potent Antibreast Cancer Agents by Supriya Singh, Sucheta Das, Anubhuti Pandey, Sarvesh Paliwal, Rajeev Singh

“…So, with an aim to elucidate the important features responsible for their activity, QSAR studies on breast cancer cell line using stepwise multiple linear regressions, partial least square, and neural network were performed. …”
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Analysis and Alternate Selection of Nanopowder Modifiers to Improve a Special Protective Coating System by S. P. Bardakhanov, V. N. Goverdovskiy, C.-M. Lee, O. C. Lee, V. T. Lygdenov

“…This paper presents a practical approach for rational choice of silica nanopowders as modifiers to control and improve the performance of protective coating systems operating in harsh environmental conditions. …”
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Impact of Normal Lung Volume Choices on Radiation Pneumonitis Risk Prediction in Locally Non-small Cell Lung Cancer Radiation Therapy by Alyssa Gadsby, MS, Tian Liu, PhD, Robert Samstein, MD, Jiahan Zhang, PhD, Yang Lei, PhD, Kenneth E. Rosenzweig, MD, Ming Chao, PhD

“…The machine learning models indicated that defining normal lung volume as TL-PTV yielded the highest predictive performance for RP2 risk. …”
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