---
# System prepended metadata

title: Background lit rev on models
tags: [models, references]

---

# Background lit rev on models

###### tags: `references`, `models`

## Papers 

- (Schroeder et al. 2020) MorphoCluster: Efficient Annotation of Plankton images by Clustering
https://arxiv.org/abs/2005.01595
Model: **ResNet18**
Github: https://github.com/morphocluster

- (Ellen et al. 2019) Improving plankton image classification using context metadata
https://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lom3.10324
Model: **VGG-16**

- (Lumini et al. 2019) Deep Learning for Plankton and Coral Classification
https://arxiv.org/ftp/arxiv/papers/1908/1908.05489.pdf (pdf)
https://arxiv.org/abs/1908.05489 (online)
Tested: **AlexNet, GoogleNet, InceptionV3, VGGNet, ResNet50, ResNet101, DenseNet, MobileNetV2, NasNet**
Key messages: "The experimental results show that the best stand-alone model for most of the target datasets is **DenseNet**. [...] We show how to create an **ensemble** which improves the performance of the best single model."

- (Li et al. 2021) Plankton Detection with Adversarial Learning and a Densely Connected Deep Learning Model for Class Imbalanced Distribution
https://www.mdpi.com/2077-1312/9/6/636/pdf (pdf)
https://doi.org/10.3390/jmse9060636 (online)
Key message: Nice review of models that have been tested already.

- (Cheng et al. 2019) Enhanced convolutional neural network for plankton identification and enumeration
[pdf](https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0219570&type=printable )
[online](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219570)
Key messages: "Among the selected CNN models, the ResNet50 performed the best."
Tested: **AlexNet, VGG16, VGG19, GoogLeNet, and ResNet**

- (Bello et al., 2021) Revisiting ResNets: Improved Training and Scaling Strategies
Model: **ResNet-RS-420**
https://arxiv.org/pdf/2103.07579 (pdf)
https://arxiv.org/abs/2103.07579 (online)
Github: https://github.com/tensorflow/tpu/tree/master/models/official/resnet/resnet_rs

- (Chen et al. 2019) Dynamic Convolution: Attention over Convolution Kernels
Model: **ResNet18**
https://arxiv.org/pdf/1912.03458v2.pdf (pdf)
https://arxiv.org/abs/1912.03458v2 (online)


# Size images
- https://blog.roboflow.com/you-might-be-resizing-your-images-incorrectly/
- https://benanne.github.io/2015/03/17/plankton.html
# Monochrome


## Other references we stumbled across
(Zheng et al. 2017) Automatic plankton image classification combining multiple view features via multiple kernel learning
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1954-8

StyleGAN
https://www.mdpi.com/2077-1312/9/6/636/pdf