EfficientNet-PyTorch VS BIOBSS

Compare EfficientNet-PyTorch vs BIOBSS and see what are their differences.

EfficientNet-PyTorch

A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!) (by lukemelas)
efficientnet-pytorch Imagenet feature-extraction pretrained-models
Source Code
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BIOBSS

A package for processing signals recorded using wearable sensors, such as Electrocardiogram (ECG), Photoplethysmogram (PPG), Electrodermal activity (EDA) and 3-axis acceleration (ACC). (by obss)
acceleration ecg eda electrocardiography electrodermal-activity feature-extraction galvanic-skin-response heart-rate-variability hrv photoplethysmography ppg signal-processing
Source Code
biobss.readthedocs.io
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EfficientNet-PyTorch BIOBSS
2 1
7,715 94
- -
0.0 0.6
about 2 years ago 4 days ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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EfficientNet-PyTorch

Posts with mentions or reviews of EfficientNet-PyTorch. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-02.
  • [D] MCDropout and CNNs
    2 projects | /r/MachineLearning | 2 Mar 2022
    I used this with the popular pytorch implementation of EfficientNet. You can see what I'm talking about here https://github.com/lukemelas/EfficientNet-PyTorch/blob/master/efficientnet_pytorch/model.py on line 127. Once you understand this code it is pretty straightforward to modify your forward pass to allow "stochastic depth" during inference.
  • [P] Backprop: a library to easily finetune and use state-of-the-art models
    2 projects | /r/MachineLearning | 22 Mar 2021
    I dont see you credit the author of https://github.com/lukemelas/EfficientNet-PyTorch yet you're using his implementation for efficientnet.

BIOBSS

Posts with mentions or reviews of BIOBSS. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing EfficientNet-PyTorch and BIOBSS you can also consider the following projects:

segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.

NeuroKit - NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

MLclf - mini-imagenet and tiny-imagent dataset transformation for traditional classification task and also for the format for few-shot learning / meta-learning tasks

PulseSensorPlayground - A PulseSensor library (for Arduino) that collects our most popular projects in one place.

kiri - Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

DropoutUncertaintyExps - Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

hrv-analysis - Package for Heart Rate Variability analysis in Python

EfficientNet-PyTorch vs segmentation_models.pytorch BIOBSS vs NeuroKit EfficientNet-PyTorch vs MLclf BIOBSS vs PulseSensorPlayground EfficientNet-PyTorch vs kiri BIOBSS vs towhee EfficientNet-PyTorch vs DropoutUncertaintyExps BIOBSS vs hrv-analysis