AIMC Topic: Algorithms

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DARC: Deep adaptive regularized clustering for histopathological image classification.

Medical image analysis
In recent years, deep learning as a state-of-the-art machine learning technique has made great success in histopathological image classification. However, most of deep learning approaches rely heavily on the substantial task-specific annotations, whi...

A Lightweight Network for Point Cloud Analysis via the Fusion of Local Features and Distribution Characteristics.

Sensors (Basel, Switzerland)
Effectively integrating the local features and their spatial distribution information for more effective point cloud analysis is a subject that has been explored for a long time. Inspired by convolutional neural networks (CNNs), this paper studies th...

Deep Learning-Based Defect Prediction for Mobile Applications.

Sensors (Basel, Switzerland)
Smartphones have enabled the widespread use of mobile applications. However, there are unrecognized defects of mobile applications that can affect businesses due to a negative user experience. To avoid this, the defects of applications should be dete...

A Multiobjective Hybrid Optimization Algorithm for Path Planning of Coal Mine Patrol Robot.

Computational intelligence and neuroscience
In the complex underground environment, the paths planned for coal mine patrol robot are often too long and unsmooth under the influence of low visibility and poor road conditions. To solve the problems, this paper improves the hybrid algorithm betwe...

An Intelligent Fusion Model with Portfolio Selection and Machine Learning for Stock Market Prediction.

Computational intelligence and neuroscience
Developing reliable equity market models allows investors to make more informed decisions. A trading model can reduce the risks associated with investment and allow traders to choose the best-paying stocks. However, stock market analysis is complicat...

Prediction of Motor Outcome of Stroke Patients Using a Deep Learning Algorithm with Brain MRI as Input Data.

European neurology
BACKGROUND: Deep learning techniques can outperform traditional machine learning techniques and learn from unstructured and perceptual data, such as images and languages. We evaluated whether a convolutional neural network (CNN) model using whole axi...

Real-time, in vivo skin cancer triage by laser-induced plasma spectroscopy combined with a deep learning-based diagnostic algorithm.

Journal of the American Academy of Dermatology
BACKGROUND: Although various skin cancer detection devices have been proposed, most of them are not used owing to their insufficient diagnostic accuracies. Laser-induced plasma spectroscopy (LIPS) can noninvasively extract biochemical information of ...

Exploring Built-Up Indices and Machine Learning Regressions for Multi-Temporal Building Density Monitoring Based on Landsat Series.

Sensors (Basel, Switzerland)
Uncontrolled built-up area expansion and building densification could bring some detrimental problems in social and economic aspects such as social inequality, urban heat islands, and disturbance in urban environments. This study monitored multi-deca...

A Robust Deep Neural Network for Rolling Element Fault Diagnosis under Various Operating and Noisy Conditions.

Sensors (Basel, Switzerland)
This study proposes a new intelligent diagnostic method for bearing faults in rotating machinery. The method uses a combination of nonlinear mode decomposition based on the improved fast kurtogram, gramian angular field, and convolutional neural netw...