# Biomedical Signal Processing and Control

**Type:** Journals  
**Canonical URL:** https://scholariq.org/journals/biomedical-signal-processing-and-control/

## Facts

| Field | Value |
| --- | --- |
| Open Access | false |
| ISSN-L | 1746-8094 |
| ISSNs | 1746-8094,1746-8108 |
| OpenAlex ID | https://openalex.org/S8427965 |
| Publisher | Elsevier BV |

## Journal papers

Showing 12 of 32.

- [Automated diagnosis of epileptic EEG using entropies](https://scholariq.org/papers/automated-diagnosis-of-epileptic-eeg-using-entropies/)
- [Stress and anxiety detection using facial cues from videos](https://scholariq.org/papers/stress-and-anxiety-detection-using-facial-cues-from-videos/)
- [Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG](https://scholariq.org/papers/intra-and-inter-epoch-temporal-context-network-iitnet-using-sub-epoch-features/)
- [REG-ICA: A hybrid methodology combining Blind Source Separation and regression techniques for the rejection of ocular artifacts](https://scholariq.org/papers/reg-ica-a-hybrid-methodology-combining-blind-source-separation-and-regression/)
- [An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images](https://scholariq.org/papers/an-efficient-deep-learning-scheme-to-detect-breast-cancer-using-mammogram-and/)
- [ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images](https://scholariq.org/papers/resdo-unet-a-deep-residual-network-for-accurate-retinal-vessel-segmentation-from/)
- [High accuracy hybrid CNN classifiers for breast cancer detection using mammogram and ultrasound datasets](https://scholariq.org/papers/high-accuracy-hybrid-cnn-classifiers-for-breast-cancer-detection-using-mammogram/)
- [Multi-class classification of brain tumour magnetic resonance images using multi-branch network with inception block and five-fold cross validation deep learning framework](https://scholariq.org/papers/multi-class-classification-of-brain-tumour-magnetic-resonance-images-using-multi/)
- [Deep learning based efficient epileptic seizure prediction with EEG channel optimization](https://scholariq.org/papers/deep-learning-based-efficient-epileptic-seizure-prediction-with-eeg-channel/)
- [Brain tumor classification using the modified ResNet50 model based on transfer learning](https://scholariq.org/papers/brain-tumor-classification-using-the-modified-resnet50-model-based-on-transfer/)
- [DSP-based arrhythmia classification using wavelet transform and probabilistic neural network](https://scholariq.org/papers/dsp-based-arrhythmia-classification-using-wavelet-transform-and-probabilistic/)
- [Optimum spectrum mask based medical image fusion using Gray Wolf Optimization](https://scholariq.org/papers/optimum-spectrum-mask-based-medical-image-fusion-using-gray-wolf-optimization/)

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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.