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NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks.

IEEE transactions on visualization and computer graphics
Existing research on making sense of deep neural networks often focuses on neuron-level interpretation, which may not adequately capture the bigger picture of how concepts are collectively encoded by multiple neurons. We present Neurocartography, an ...

Machine learning in systematic reviews: Comparing automated text clustering with Lingo3G and human researcher categorization in a rapid review.

Research synthesis methods
Systematic reviews are resource-intensive. The machine learning tools being developed mostly focus on the study identification process, but tools to assist in analysis and categorization are also needed. One possibility is to use unsupervised automat...

Clustering by Errors: A Self-Organized Multitask Learning Method for Acoustic Scene Classification.

Sensors (Basel, Switzerland)
Acoustic scene classification (ASC) tries to inference information about the environment using audio segments. The inter-class similarity is a significant issue in ASC as acoustic scenes with different labels may sound quite similar. In this paper, t...

Deep Stacking Network for Intrusion Detection.

Sensors (Basel, Switzerland)
Preventing network intrusion is the essential requirement of network security. In recent years, people have conducted a lot of research on network intrusion detection systems. However, with the increasing number of advanced threat attacks, traditiona...

Unsupervised Event Graph Representation and Similarity Learning on Biomedical Literature.

Sensors (Basel, Switzerland)
The automatic extraction of biomedical events from the scientific literature has drawn keen interest in the last several years, recognizing complex and semantically rich graphical interactions otherwise buried in texts. However, very few works revolv...

Brain tissue segmentation via non-local fuzzy c-means clustering combined with Markov random field.

Mathematical biosciences and engineering : MBE
The segmentation and extraction of brain tissue in magnetic resonance imaging (MRI) is a meaningful task because it provides a diagnosis and treatment basis for observing brain tissue development, delineating lesions, and planning surgery. However, M...

Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach.

BMC medical genomics
BACKGROUND: Mutation processes leave different signatures in genes. For single-base substitutions, previous studies have suggested that mutation signatures are not only reflected in mutation bases but also in neighboring bases. However, because of th...

Cluster-Based Mutual Fund Classification and Price Prediction Using Machine Learning for Robo-Advisors.

Computational intelligence and neuroscience
The rise of FinTech has been meteoric in China. Investing in mutual funds through robo-advisor has become a new innovation in the wealth management industry. In recent years, machine learning, especially deep learning, has been widely used in the fin...

Application of the Deep Learning Algorithm and Similarity Calculation Model in Optimization of Personalized Online Teaching System of English Course.

Computational intelligence and neuroscience
This study provides an in-depth study and analysis of English course recommendation techniques through a combination of bee colony algorithm and neural network algorithm. In this study, the acquired text is trained with a document vector by a deep le...

Clustering-Based Plane Segmentation Neural Network for Urban Scene Modeling.

Sensors (Basel, Switzerland)
Urban scene modeling is a challenging but essential task for various applications, such as 3D map generation, city digitization, and AR/VR/metaverse applications. To model man-made structures, such as roads and buildings, which are the major componen...