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Entropy

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Landslide susceptibility mapping using an entropy index-based negative sample selection strategy: A case study of Luolong county.

PloS one
Landslides constitute a significant geological hazard in China, particularly in high-altitude regions like the Himalayas, where the challenging environmental conditions impede field surveys. This research utilizes the IOE model to refine non-landslid...

EVOLVE: A Web Platform for AI-Based Protein Mutation Prediction and Evolutionary Phase Exploration.

Journal of chemical information and modeling
While predicting structure-function relationships from sequence data is fundamental in biophysical chemistry, identifying prospective single-point and collective mutation sites in proteins can help us stay ahead in understanding their potential effec...

Complexity Analysis based on Parietal Fuzzy Entropy to Facilitate ADHD Diagnosis in Young Children.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Attention deficit hyperactivity disorder (ADHD) is the most common condition affecting the development of neurons in children. Therefore, early and accurate diagnosis of ADHD in young children is of paramount importance. In this study, the 8-channel ...

Non-customized data asset evaluation based on knowledge graph and value entropy.

PloS one
With the rapid expansion of non-customized data assets, developing reliable and objective methods for their valuation has become essential. However, current evaluation techniques often face challenges such as incomplete indicator systems and an over-...

Global Cross-Entropy Loss for Deep Face Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Contemporary deep face recognition techniques predominantly utilize the Softmax loss function, designed based on the similarities between sample features and class prototypes. These similarities can be categorized into four types: in-sample target si...

Complex quantized minimum error entropy with fiducial points: theory and application in model regression.

Neural networks : the official journal of the International Neural Network Society
Minimum error entropy with fiducial points (MEEF) has gained significant attention due to its excellent performance in mitigating the adverse effects of non-Gaussian noise in the fields of machine learning and signal processing. However, the original...

Improving generalization of neural Vehicle Routing Problem solvers through the lens of model architecture.

Neural networks : the official journal of the International Neural Network Society
Neural models produce promising results when solving Vehicle Routing Problems (VRPs), but may often fall short in generalization. Recent attempts to enhance model generalization often incur unnecessarily large training cost or cannot be directly appl...

Leveraging vision transformers and entropy-based attention for accurate micro-expression recognition.

Scientific reports
Micro-expressions are difficult to fake and inherently truthful, making micro-expression recognition technology widely applicable across various domains. With the development of artificial intelligence, the accuracy and efficiency of micro-expression...

Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.

Translational psychiatry
Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical symptoms and genetic factors, often resulting in misdiagnosis and suboptimal treatment outcomes. This study aimed to identify EEG-based biomarkers tha...

Integrating lightweight convolutional neural network with entropy-informed channel attention and adaptive spatial attention for OCT-based retinal disease classification.

Computers in biology and medicine
This article proposes an effective and lightweight contextual convolutional neural network architecture called LOCT-Net for classifying retinal diseases. The LOCT-Net adopts nested residual blocks to capture the local patterns from the optical cohere...