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code/requirements.txt

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code/test.py

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linkreview.md

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# For Introduction
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| Title | Year | Source | Description |
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| :--------------------------------------------------------------------- | ---: | :--------------------------------------------------------------------------------------------------------------- | :---------- |
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| Brain tumor detection using CNN, AlexNet & GoogLeNet ensembling learning approaches | 2023 | [paper](https://www.researchgate.net/publication/369308467_Brain_tumor_detection_using_CNN_AlexNet_GoogLeNet_ensembling_learning_approaches)| - |
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| A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions | 2021 | [paper](https://arxiv.org/pdf/2006.02903) | - |
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| Title | Year | Source | Description |
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| :---------------------------------------------------------------------------------- | ---: | :------------------------------------------------------------------------------------------------------------------------------------------- | :---------- |
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| Brain tumor detection using CNN, AlexNet & GoogLeNet ensembling learning approaches | 2023 | [paper](https://www.researchgate.net/publication/369308467_Brain_tumor_detection_using_CNN_AlexNet_GoogLeNet_ensembling_learning_approaches) | - |
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| A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions | 2021 | [paper](https://arxiv.org/pdf/2006.02903) | - |
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| NSgGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search | 2020 | [paper](https://arxiv.org/pdf/2007.10396) | - |
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| Evolutionary Architecture Search for Graph Neural Networks | 2020 | [paper](https://arxiv.org/pdf/2009.10199) | - |
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| MoSegNAS: Surrogate-assisted Multi-objective Neural Architecture Search for Real-time Semantic Segmentation | 2022 | [paper](https://arxiv.org/pdf/2208.06820) | - |
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| Convolutional Neural Networks based Lung Nodule Classification: A Surrogate-Assisted Evolutionary Algorithm for Hyperparameter Optimization | 2015 | [paper](https://shiruipan.github.io/publication/tevc-21-zhang/tevc-21-zhang.pdf) | - |
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| Combining global and local surrogate models to accelerate evolutionary optimization | 2006 | [paper](https://www.researchgate.net/publication/3421747_Combining_global_and_local_surrogate_models_to_accelerate_evolutionary_optimization_IEEE_Trans_Syst_Man_Cybern_Part_C_Appl_Rev) | - |
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| A Survey on Evolutionary Neural Architecture Search | 2022 | [paper](https://arxiv.org/pdf/2008.10937) | - |
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# Others

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