{ "id": 240283, "title": "Research Papers with Model Benchmarks", "url": "/competitions/siim-covid19-detection/discussion/240283", "author_name": "Manav", "post_date": "2021-05-19T06:53:07.556000", "votes": 3, "comment_count": 0, "views": 0, "content": "

Hi Fellow Kagglers,

\n

As a starting point / reference model benchmark we can refer to these links below where various CNN architecture and Transfer learning methods have been applied and model performances are summarized:-

\n
    \n
  1. Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study (Section-3)
    2. \n
  2. COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images
    3. \n
  3. Deep Learning for Screening COVID-19 using Chest X-Ray Images
    4. \n
  4. Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy
    5. \n
  5. Automated detection of COVID-19 cases using deep neural networks with X-ray images
    6. \n
\n

My understanding:- Preprocessing and augmentation is going to play a major role in performance of a single model.

\n

I will add more papers when I find them.

\n

Thanks and all the best 😊👍

", "messages": [ { "id": 1314417, "postDate": "2021-05-19T06:53:07.557Z", "content": "

Hi Fellow Kagglers,

\n

As a starting point / reference model benchmark we can refer to these links below where various CNN architecture and Transfer learning methods have been applied and model performances are summarized:-

\n
    \n
  1. Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study (Section-3)
    2. \n
  2. COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images
    3. \n
  3. Deep Learning for Screening COVID-19 using Chest X-Ray Images
    4. \n
  4. Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy
    5. \n
  5. Automated detection of COVID-19 cases using deep neural networks with X-ray images
    6. \n
\n

My understanding:- Preprocessing and augmentation is going to play a major role in performance of a single model.

\n

I will add more papers when I find them.

\n

Thanks and all the best 😊👍

", "rawMarkdown": "Hi Fellow Kagglers,\n\nAs a starting point / reference model benchmark we can refer to these links below where various CNN architecture and Transfer learning methods have been applied and model performances are summarized:-\n1. [Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study](https://www.sciencedirect.com/science/article/pii/S1746809420304717) (Section-3)\n2. [COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images](https://www.nature.com/articles/s41598-020-76550-z)\n3. [Deep Learning for Screening COVID-19 using Chest X-Ray Images](https://arxiv.org/pdf/2004.10507.pdf)\n4. [Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy](https://eurradiolexp.springeropen.com/articles/10.1186/s41747-020-00203-z)\n5. [Automated detection of COVID-19 cases using deep neural networks with X-ray images](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187882/)\n\nMy understanding:- Preprocessing and augmentation is going to play a major role in performance of a single model.\n\nI will add more papers when I find them.\n\nThanks and all the best 😊👍", "votes": 3 } ], "comments": [], "raw_markdown_by_id": { "1314417": "Hi Fellow Kagglers,\n\nAs a starting point / reference model benchmark we can refer to these links below where various CNN architecture and Transfer learning methods have been applied and model performances are summarized:-\n1. [Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study](https://www.sciencedirect.com/science/article/pii/S1746809420304717) (Section-3)\n2. [COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images](https://www.nature.com/articles/s41598-020-76550-z)\n3. [Deep Learning for Screening COVID-19 using Chest X-Ray Images](https://arxiv.org/pdf/2004.10507.pdf)\n4. [Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy](https://eurradiolexp.springeropen.com/articles/10.1186/s41747-020-00203-z)\n5. [Automated detection of COVID-19 cases using deep neural networks with X-ray images](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187882/)\n\nMy understanding:- Preprocessing and augmentation is going to play a major role in performance of a single model.\n\nI will add more papers when I find them.\n\nThanks and all the best 😊👍" } }