NSTL国家科技图书文献中心

1. Prediction of the higher heating value of biomass based on multiple classification methods NSTL国家科技图书文献中心

Zhao, Chenxi | Lu, Xueying ... - 《Biomass Conversion and Biorefinery》 - 2025,15(4) - 5183～5191 - 共9页

摘要： methods: biomass categories classification, K-means | the classification* methods was better than that of* | (HHV) of biomass by experimental methods* is time* | classified according to three different classification | clustering classification, and ash and volatile matter (VM

关键词： Higher heating value | Prediction | Classification | Biomass categories | K-means clustering | Proximate analysis

2. A Study on Detection and Classification Methods for Red Tide Phytoplankton Using Deep Learning NSTL国家科技图书文献中心

Tomoka Kawano | Masahiro Migita ... - 《International Workshop on Advanced Imaging Technology (IWAIT) 2025》 - International Workshop on Advanced Imaging Technology - 2025, - 135101R.1～135101R.6 - 共6页

摘要： object detection methods* to classify various marine* | Red tides are phenomena caused by the abnormal | proliferation of marine plankton, leading to massive fish | deaths and significant damage to the fishing industry | . Currently, detection and quantification of plankton

关键词： Red tide | Deep learning | Object detection | RetinaNet | Faster r-CNN | DETR | YOLO

3. Research on short text information mining and classification methods for social media NSTL国家科技图书文献中心

Tingting Wang - 《International journal of computational systems engineering》 - 2025,9(1) - 31～39 - 共9页

摘要：, with better classification* outcomes. The precision of* | 29.85% in the classification* of short textbooks in* | The internet era has brought massive | information output and dissemination, and social media | , mainly represented by WeChat and Weibo, have gradually

关键词： social media | short text | information classification | graph convolutional network | attention mechanism

4. Deep Learning Methods for fMRI Classification NSTL国家科技图书文献中心

Luca Barillaro | Giuseppe Agapito - 《Numerical Computations,Part III》 - International Conference on Numerical Computations: Theory and Algorithms - 2025, - 15～25 - 共11页

摘要：-based methods* for the classification of functional* | reviews deep learning methods for fMRI classification | fMRI datasets. The classification* task is essential* | This paper aims to review some deep learning | Magnetic Resonance Imaging (fMRI) brain images. fMRI is

关键词： FMRI | Deep learning | Medical imaging

5. Federated learning methods for collaborative multiclass classification of dry beans NSTL国家科技图书文献中心

Gaur, Ankush Kumar | Valan, J. Arul - 《Genetic Resources and Crop Evolution》 - 2025,72(2) - 1421～1439 - 共19页

摘要： methods for the collaborative multiclass classification | classification within a FL setup. The study evaluates the | context of multiclass classification, comparing them | comparable, and in some cases superior, classification | Federated learning (FL), a decentralized

关键词： Federated learning | Federated optimization | Multiclass classification | Collaborative learning

6. A review of convolutional neural network based methods for medical image classification NSTL国家科技图书文献中心

Chen C. | Mat Isa N.A.... - 《Computers in Biology and Medicine》 - 2025,185 - Article 109507～Article 109507 - 共41页

摘要： reviews CNN-based medical image classification methods | analysis of the methods* used therein. Based on the* | the field of medical image classification* are* | image classification, which is also the current | explainability, and their role in improving classification

关键词： CNN | Convolutional neural network | Deep learning | Medical image classification | Medical image processing

7. Classification of similar electronic components by transfer learning methods NSTL国家科技图书文献中心

Goeksu Tas - 《Engineering Applications of Artificial Intelligence》 - 2025,139(Jan. Pt.B) - 109658.1～109658.11 - 共11页

摘要： addition to the transfer learning methods, the parallel | solve the classification* problem. In addition to the* | evaluation methods. The number of parameters and runtime | Proper selection of electronic components and | automated component identification is critical for fast

关键词： Internet of Things | Transfer learning | Electronic components | Deep learning | Image classification

8. Hierarchical Classification of Frontotemporal Dementia Subtypes Utilizing Tabular-to-Image Data Conversion with Deep Learning Methods NSTL国家科技图书文献中心

Km Poonam | Venkata Sathwik Kotr...... - 《Pattern Recognition,Part XI》 - International Conference on Pattern Recognition - 2025, - 386～401 - 共16页

摘要： novel hierarchical classification* methods that enhance* | Neuroimaging Initiative database. Innovative methods* are* | classification, especially when limited to tabular data. To | hierarchical approach over flat machine learning methods* and* | classification with image-based technique compared to best flat

关键词： Frontotemporal dementia | Hierarchical classification | Tabular-to-Images conversion | Deep-Learning

9. A lightweight machine learning methods for malware classification NSTL国家科技图书文献中心

Farfoura, Mahmoud E. | Mashal, Ibrahim ... - 《Cluster computing》 - 2025,28(1) - 共14页 - 被引量：1

摘要： malware classification. The proposed solutions are | edge computing systems. These methods* allow for real* | Today's Information Technology landscape is | rapidly evolving. Cyber professionals are increasingly | concerned about maintaining security and privacy. Research

关键词： Malware | Anti-malware | Machine learning | Dimensionality reduction | Random forest | Logistic regression | SVM | LGBM | Classification | Matrix block mean downsampling

10. Data Mining in Credit Card Approval: Feature Importance Testing Comparison NSTL国家科技图书文献中心

Qingyu Ye | Simon Fong ... - 《Intelligent Data Engineering and Automated Learning - IDEAL 2024,Part II》 - International Conference on Intelligent Data Engineering and Automated Learning - 2025, - 543～554 - 共12页

摘要： three classification* methods, assessing their* | techniques and classification* methods in refining credit* | specific focus on credit card approval classification. We | card approval classification* tasks.* | Understanding the significance of features in

摘要： methods: biomass categories classification, K-means | the classification* methods was better than that of* | (HHV) of biomass by experimental methods* is time* | classified according to three different classification | clustering classification, and ash and volatile matter (VM

关键词： Higher heating value | Prediction | Classification | Biomass categories | K-means clustering | Proximate analysis

摘要： object detection methods* to classify various marine* | Red tides are phenomena caused by the abnormal | proliferation of marine plankton, leading to massive fish | deaths and significant damage to the fishing industry | . Currently, detection and quantification of plankton

关键词： Red tide | Deep learning | Object detection | RetinaNet | Faster r-CNN | DETR | YOLO

摘要：, with better classification* outcomes. The precision of* | 29.85% in the classification* of short textbooks in* | The internet era has brought massive | information output and dissemination, and social media | , mainly represented by WeChat and Weibo, have gradually

关键词： social media | short text | information classification | graph convolutional network | attention mechanism

摘要：-based methods* for the classification of functional* | reviews deep learning methods for fMRI classification | fMRI datasets. The classification* task is essential* | This paper aims to review some deep learning | Magnetic Resonance Imaging (fMRI) brain images. fMRI is

关键词： FMRI | Deep learning | Medical imaging

摘要： methods for the collaborative multiclass classification | classification within a FL setup. The study evaluates the | context of multiclass classification, comparing them | comparable, and in some cases superior, classification | Federated learning (FL), a decentralized

关键词： Federated learning | Federated optimization | Multiclass classification | Collaborative learning

摘要： reviews CNN-based medical image classification methods | analysis of the methods* used therein. Based on the* | the field of medical image classification* are* | image classification, which is also the current | explainability, and their role in improving classification

关键词： CNN | Convolutional neural network | Deep learning | Medical image classification | Medical image processing

摘要： addition to the transfer learning methods, the parallel | solve the classification* problem. In addition to the* | evaluation methods. The number of parameters and runtime | Proper selection of electronic components and | automated component identification is critical for fast

关键词： Internet of Things | Transfer learning | Electronic components | Deep learning | Image classification

关键词： Frontotemporal dementia | Hierarchical classification | Tabular-to-Images conversion | Deep-Learning

摘要： malware classification. The proposed solutions are | edge computing systems. These methods* allow for real* | Today's Information Technology landscape is | rapidly evolving. Cyber professionals are increasingly | concerned about maintaining security and privacy. Research

关键词： Malware | Anti-malware | Machine learning | Dimensionality reduction | Random forest | Logistic regression | SVM | LGBM | Classification | Matrix block mean downsampling

摘要： three classification* methods, assessing their* | techniques and classification* methods in refining credit* | specific focus on credit card approval classification. We | card approval classification* tasks.* | Understanding the significance of features in

关键词： Feature importance | Data mining | Credit card approval | Classification methods | Financial risk analysis

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： methods: biomass categories classification, K-means | the classification methods was better than that of | (HHV) of biomass by experimental methods is time | classified according to three different classification | clustering classification, and ash and volatile matter (VM

关键词： Higher heating value | Prediction | Classification | Biomass categories | K-means clustering | Proximate analysis

摘要： object detection methods to classify various marine | Red tides are phenomena caused by the abnormal | proliferation of marine plankton, leading to massive fish | deaths and significant damage to the fishing industry | . Currently, detection and quantification of plankton

关键词： Red tide | Deep learning | Object detection | RetinaNet | Faster r-CNN | DETR | YOLO

摘要：, with better classification outcomes. The precision of | 29.85% in the classification of short textbooks in | The internet era has brought massive | information output and dissemination, and social media | , mainly represented by WeChat and Weibo, have gradually

关键词： social media | short text | information classification | graph convolutional network | attention mechanism

摘要：-based methods for the classification of functional | reviews deep learning methods for fMRI classification | fMRI datasets. The classification task is essential | This paper aims to review some deep learning | Magnetic Resonance Imaging (fMRI) brain images. fMRI is

关键词： FMRI | Deep learning | Medical imaging

摘要： methods for the collaborative multiclass classification | classification within a FL setup. The study evaluates the | context of multiclass classification, comparing them | comparable, and in some cases superior, classification | Federated learning (FL), a decentralized

关键词： Federated learning | Federated optimization | Multiclass classification | Collaborative learning

摘要： reviews CNN-based medical image classification methods | analysis of the methods used therein. Based on the | the field of medical image classification are | image classification, which is also the current | explainability, and their role in improving classification

关键词： CNN | Convolutional neural network | Deep learning | Medical image classification | Medical image processing

摘要： addition to the transfer learning methods, the parallel | solve the classification problem. In addition to the | evaluation methods. The number of parameters and runtime | Proper selection of electronic components and | automated component identification is critical for fast

关键词： Internet of Things | Transfer learning | Electronic components | Deep learning | Image classification

关键词： Frontotemporal dementia | Hierarchical classification | Tabular-to-Images conversion | Deep-Learning

摘要： malware classification. The proposed solutions are | edge computing systems. These methods allow for real | Today's Information Technology landscape is | rapidly evolving. Cyber professionals are increasingly | concerned about maintaining security and privacy. Research

关键词： Malware | Anti-malware | Machine learning | Dimensionality reduction | Random forest | Logistic regression | SVM | LGBM | Classification | Matrix block mean downsampling

摘要： three classification methods, assessing their | techniques and classification methods in refining credit | specific focus on credit card approval classification. We | card approval classification tasks. | Understanding the significance of features in

关键词： Feature importance | Data mining | Credit card approval | Classification methods | Financial risk analysis

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： methods: biomass categories classification, K-means | the classification* methods was better than that of* | (HHV) of biomass by experimental methods* is time* | classified according to three different classification | clustering classification, and ash and volatile matter (VM

摘要： object detection methods* to classify various marine* | Red tides are phenomena caused by the abnormal | proliferation of marine plankton, leading to massive fish | deaths and significant damage to the fishing industry | . Currently, detection and quantification of plankton

摘要：, with better classification* outcomes. The precision of* | 29.85% in the classification* of short textbooks in* | The internet era has brought massive | information output and dissemination, and social media | , mainly represented by WeChat and Weibo, have gradually

摘要：-based methods* for the classification of functional* | reviews deep learning methods for fMRI classification | fMRI datasets. The classification* task is essential* | This paper aims to review some deep learning | Magnetic Resonance Imaging (fMRI) brain images. fMRI is

摘要： reviews CNN-based medical image classification methods | analysis of the methods* used therein. Based on the* | the field of medical image classification* are* | image classification, which is also the current | explainability, and their role in improving classification

摘要： addition to the transfer learning methods, the parallel | solve the classification* problem. In addition to the* | evaluation methods. The number of parameters and runtime | Proper selection of electronic components and | automated component identification is critical for fast

摘要： malware classification. The proposed solutions are | edge computing systems. These methods* allow for real* | Today's Information Technology landscape is | rapidly evolving. Cyber professionals are increasingly | concerned about maintaining security and privacy. Research

摘要： three classification* methods, assessing their* | techniques and classification* methods in refining credit* | specific focus on credit card approval classification. We | card approval classification* tasks.* | Understanding the significance of features in