Estimation of the High-Frequency Feature Slope in Gravitational Wave Signals from Core Collapse Supernovae Using Machine Learning by Alejandro Casallas-Lagos, Javier M. Antelis, Claudia Moreno, Ramiro Franco-Hernández

“…We conducted an in-depth exploration of the use of different machine learning (ML) for regression algorithms, including Linear, Ridge, LASSO, Bayesian Ridge, Decision Tree, and a variety of Deep Neural Network (DNN) architectures, to estimate the slope of the high-frequency feature (HFF), a prominent emergent feature found in the gravitational wave (GW) signals of core collapse supernovae (CCSN). …”
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Multi-grained pooling network for age estimation in degraded low-resolution images by Hang-Xing Zang, Qinyin Xiao

“…To address the limitation, we propose the Multi-Grained Pooling Network (MGP-Net), a novel architecture that effectively captures multi-grained information during the downsampling process, preserving essential features for age estimation. …”
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Feature Augmentation of Classifiers Using Learning Time Series Shapelets Transformation for Night Setback Classification of District Heating Substations by Fan Zhang, Chris Bales, Hasan Fleyeh

“…To evaluate the effectiveness of the proposed approach, data of 10 anonymous substations in Sweden are used in the case study. …”
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Exploring the capabilities of hyperspectral remote sensing for soil texture evaluation by Mohammad Hosseinpour-Zarnaq, Mahmoud Omid, Fereydoon Sarmadian, Hassan Ghasemi-Mobtaker, Reza Alimardani, Pouya Bohlol

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Automatic Sleep Staging Method Using EEG Based on STFT and Residual Network by Ran Zhang, Rui Jiang, Haowei Hu, Ying Gao, Wei Xia, Boming Song

“…Subsequently, the deep-seated temporal and spectral features of sleep stages are unearthed and learned through an improved ResNet-18 residual network, facilitating the automated classification of sleep stages. …”
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PATNet: Permute attention and transformer-enhanced network for segmentation of musculoskeletal ultrasound images by Yating Wu, Feng Bu, Jin Tian, Li Zhao, Guangfei Yang, Jianming Lu

“…To address the above issues, this paper proposes a deep learning model called PATNet (Permute Attention and Transformer-Enhanced Network for Segmentation of Musculoskeletal Ultrasound Images). …”
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Temporal Attention-Enhanced Stacking Networks: Revolutionizing Multi-Step Bitcoin Forecasting by Phumudzo Lloyd Seabe, Edson Pindza, Claude Rodrigue Bambe Moutsinga, Maggie Aphane

“…The proposed Temporal Attention-Enhanced Stacking Network (TAESN) integrates the complementary strengths of diverse machine learning algorithms while emphasizing critical temporal features, leading to substantial improvements in forecasting accuracy over traditional methods. …”
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Social Network Community Detection by Combining Self-Organizing Maps and Genetic Algorithms by Mehdi Ellouze

“…Community detection is one of these tools and aims to detect a set of entities that share some features within a social network. We have taken part in this effort, and we proposed an approach mainly based on pattern recognition techniques. …”
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High-performance glass classification using advanced machine learning and deep learning algorithms with a comprehensive feature analysis by Mohammed Bouziane, Abdelghani Bouziane, Samia Larguech, Khatir Naima, Mohammad Salman Haque, Younes Menni

“…Feature importance analysis pinpoints significant features and identifies magnesium and barium among those used to distinguish between glass types. …”
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Feature engineering on climate data with machine learning to understand time-lagging effects in pasture yield predictionGitHub by Thirunavukarasu Balasubramaniam, Wathsala Anupama Mohotti, Kenneth Sabir, Richi Nayak

“…Utilizing remote sensing and climate data, covering 196 farms (and 6885 paddocks) across Australia, we applied several machine learning techniques, including XGBoost, random forest, linear regression, deep neural networks, stacking, and bootstrapping. Our results show that incorporating averaging-based feature-engineered climate attributes significantly improves pasture yield predictions, with enhancements of up to 20.28%, 31.81%, and 31.11% across the three evaluation measures, RMSE, MAE, and R2, respectively. …”
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IW Extraction From SAR Images Based on Generative Networks With Small Datasets by B. Saheya, Xia Ren, Maoguo Gong, Xiaofeng Li

“…To address this issue, this article developed a generative adversarial network with multiscale downsampling and upsampling (GAN-MSDU) consisting of a series of adversarial networks at multiple scales. …”
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Multimodal malware classification using proposed ensemble deep neural network framework by Sadia Nazim, Muhammad Mansoor Alam, Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Su’ud

“…The effectiveness of the proposed model is verified through the evaluation metrics such as Recall (86.5%), F1-score (85.0%), and Precision (79.9%). …”
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Graph-Based COVID-19 Detection Using Conditional Generative Adversarial Network by Imran Ihsan, Azhar Imran, Tahir Sher, Mahmood Basil A. Al-Rawi, Mohammed A. Elmeligy, Muhammad Salman Pathan

“…Subsequently, a graph-based feature reconstruction technique amalgamates these extracted features across the network, culminating in a comprehensive representation. …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…Convolution Neural Networks (CNN) are best in their ability to detect rice diseases but still face challenges in generalizing equally well for all classes of disease in multiclass classification. …”
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Advanced neural network architectures for tomato leaf disease diagnosis in precision agriculture by Hritwik Ghosh, Irfan Sadiq Rahat, Md. Mintajur Rahman Emon, Md. Jisan Mashrafi, Mohammed Abdul Al Arafat Tanzin, Sachi Nandan Mohanty, Shashi Kant

“…Our approach stands out through the integration of state-of-the-art neural network architectures—VGG19, Vision Transformer (ViT), EfficientNetV2, ConvNeXt—and a novel hybrid model specifically designed to leverage the strengths of diverse architectures. …”
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Photovoltaic Hosting Capacity Assessment of Distribution Networks Considering Source–Load Uncertainty by Chao Chen, Weifeng Peng, Cheng Xie, Shufeng Dong, Yibo Hua

“…In addition, a PV power scenario generation method based on the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) is proposed, integrating physical-data dual-driven strategies to enhance the physical consistency of generated data, while incorporating a target-driven weighted sampling mechanism to improve its learning ability for key features. …”
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Comprehensive integration of diagnostic biomarker analysis and immune cell infiltration features in sepsis via machine learning and bioinformatics techniques by Liuqing Yang, Liuqing Yang, Liuqing Yang, Rui Xuan, Rui Xuan, Rui Xuan, Dawei Xu, Dawei Xu, Dawei Xu, Aming Sang, Aming Sang, Aming Sang, Jing Zhang, Jing Zhang, Jing Zhang, Yanfang Zhang, Xujun Ye, Xinyi Li, Xinyi Li, Xinyi Li

“…Following this, we integrated the DEGs with the genes from key modules as determined by Weighted Gene Co-expression Network Analysis (WGCNA), identifying 262 overlapping genes. 12 core genes were subsequently selected using three machine-learning algorithms: random forest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine-Recursive Feature Elimination (SVW-RFE). …”
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PRNet: 3D Object Detection Network-Based on Point-Region Fusion by Yufei Fu, Yuhao Guo, Hui Hu

“…In evaluations conducted on the KITTI benchmark, the method presented here surpasses prior fusion networks in detection accuracy, achieving rates of 91.95%, 81.10%, and 78.08%.…”
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Future research of supply chain resilience: Network perspectives and incorporation of more stakeholders by L. Jeff Hong, Jinzhi Li, Xiaole Wu, Shuyue Yi

“…We suggest topics including global supply chain resilience evaluation using trade networks, technology networks, and firm ownership networks, the impact of trade policies with network perspectives, design of tariff and non-tariff measures under trade agreements, domestic industry relocation, evaluating the effects of government subsidies on firms’ long-term innovation, and design of subsidy strategies for supply chain stability and resilience. …”
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Rice Leaf Nutrient Deficiency Classification System Using CAR-Capsule Network by M. Amudha, K. Brindha

“…The training and evaluation datasets are sourced from Kaggle, a freely accessible data platform. …”
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