# Entropy

**Type:** Journals  
**Canonical URL:** https://scholariq.org/journals/entropy/

## Facts

| Field | Value |
| --- | --- |
| Open Access | true |
| ISSN-L | 1099-4300 |
| ISSNs | 1099-4300 |
| OpenAlex ID | https://openalex.org/S195231649 |
| Publisher | Multidisciplinary Digital Publishing Institute |

## Journal papers

- [An Efficient DenseNet-Based Deep Learning Model for Malware Detection](https://scholariq.org/papers/an-efficient-densenet-based-deep-learning-model-for-malware-detection/)
- [Coherent Precipitation and Strengthening in Compositionally Complex Alloys: A Review](https://scholariq.org/papers/coherent-precipitation-and-strengthening-in-compositionally-complex-alloys-a/)
- [Fruit Classification by Wavelet-Entropy and Feedforward Neural Network Trained by Fitness-Scaled Chaotic ABC and Biogeography-Based Optimization](https://scholariq.org/papers/fruit-classification-by-wavelet-entropy-and-feedforward-neural-network-trained/)
- [Salient Object Detection Techniques in Computer Vision—A Survey](https://scholariq.org/papers/salient-object-detection-techniques-in-computer-vision-a-survey/)
- [Deep Neural Networks for ECG-Based Pulse Detection during Out-of-Hospital Cardiac Arrest](https://scholariq.org/papers/deep-neural-networks-for-ecg-based-pulse-detection-during-out-of-hospital/)
- [Model-Based Approaches to Active Perception and Control](https://scholariq.org/papers/model-based-approaches-to-active-perception-and-control/)
- [Effects of Near Wall Modeling in the Improved-Delayed-Detached-Eddy-Simulation (IDDES) Methodology](https://scholariq.org/papers/effects-of-near-wall-modeling-in-the-improved-delayed-detached-eddy-simulation/)
- [Driving Fatigue Detection with Three Non-Hair-Bearing EEG Channels and Modified Transformer Model](https://scholariq.org/papers/driving-fatigue-detection-with-three-non-hair-bearing-eeg-channels-and-modified/)
- [Estimating Gaussian Copulas with Missing Data with and without Expert Knowledge](https://scholariq.org/papers/estimating-gaussian-copulas-with-missing-data-with-and-without-expert-knowledge/)
- [Ensemble Entropy with Adaptive Deep Fusion for Short-Term Power Load Forecasting](https://scholariq.org/papers/ensemble-entropy-with-adaptive-deep-fusion-for-short-term-power-load-forecasting/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.