An exhaustive list of object detection papers and models by @boltcoder
\n
",
"rawMarkdown": "Placeholder for all the useful resources:\n- Past competitions solutions and notebooks\n- Research papers\n- Discussion threads. \n\nI will be posting more whenever I find something relevant and useful.\n### Competitions\n- [VinBigData Chest X-ray Abnormalities Detection](https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection)\n - **1st Place Solution**\n - Overview - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/231511 by @morizin\n - Journey of one of the team member - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229724 by @fatihozturk\n - Code - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/232393 by @morizin\n - **2nd Place Solution**\n - Overview - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229696 by @zfturbo\n - MMDetection - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229740 by @ivanpan\n - Code - https://github.com/ZFTurbo/2nd-place-solution-for-VinBigData-Chest-X-ray-Abnormalities-Detection\n - **3rd Place Solution**\n - Overview - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229769 by @scusywxy\n - Code - https://github.com/Scu-sen/VinBigData-Chest-X-ray-Abnormalities-Detection\n - **Other Solutions**\n - Compilation - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229628 by @usharengaraju\n - **Notebooks**\n - DICOM to Numpy Array - https://www.kaggle.com/raddar/convert-dicom-to-np-array-the-correct-way by @raddar\n - EDA - https://www.kaggle.com/trungthanhnguyen0502/eda-vinbigdata-chest-x-ray-abnormalities by @trungthanhnguyen0502\n - Visual In-Depth EDA- https://www.kaggle.com/dschettler8845/visual-in-depth-eda-vinbigdata-competition-data by @dschettler8845\n - BBoxes Fusion - https://www.kaggle.com/sreevishnudamodaran/vinbigdata-fusing-bboxes-coco-dataset by @sreevishnudamodaran\n- [RSNA Pneumonia Detection Challenge](https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/)\n - **1st Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/discussion/70421 by @vaillant\n - Code - https://github.com/i-pan/kaggle-rsna18\n - **2nd Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/discussion/70427 by @dmytropoplavskiy\n - Solution based on - https://github.com/yhenon/pytorch-retinanet\n - **3rd Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/discussion/70632 by @pmcheng\n - Code - https://github.com/pmcheng/rsna-pneumonia\n - **Notebooks**\n - EDA - https://www.kaggle.com/peterchang77/exploratory-data-analysis by @peterchang77 and @georges \n - More EDA - https://www.kaggle.com/gpreda/rsna-pneumonia-detection-eda by @gpreda\n - CheXNet - https://www.kaggle.com/ashishpatel26/chexnet-radiologist-level-pneumonia-detection by @ashishpatel26\n- [SIIM-ACR Pneumothorax Segmentation](https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/)\n - **1st Place Solution**\n - Overview - https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/discussion/107824 by @sneddy\n - Code - https://github.com/sneddy/pneumothorax-segmentation\n - **2nd Place Solution**\n - Overview - https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/discussion/108009 by @lanjunyelan\n - Code - https://github.com/yelanlan/Pneumothorax-Segmentation-2nd-place-solution\n - **3rd Place Solution**\n - Overview - https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/discussion/107981 by @bestfitting \n - Code - https://github.com/bestfitting/kaggle/tree/master/siim_acr\n - **Other Solutions**\n - Gold Medal - https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/discussion/108308 by @rohanrao\n - **Notebooks**\n - Starter - https://www.kaggle.com/jesperdramsch/intro-chest-xray-dicom-viz-u-nets-full-data by @jesperdramsch\n - EDA + U-Net - https://www.kaggle.com/ekhtiar/finding-pneumo-part-1-eda-and-unet by @ekhtiar\n- [RSNA STR Pulmonary Embolism Detection](https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection)\n - **1st Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection/discussion/194145 by @wowfattie\n - Code - https://github.com/GuanshuoXu/RSNA-STR-Pulmonary-Embolism-Detection\n - **2nd Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection/discussion/193401 by @vaillant\n - Code - https://github.com/i-pan/kaggle-rsna-pe\n - **3rd Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection/discussion/193424 by @moewie94\n - Code - https://github.com/moewiee/RSNA2020-Team-VinBDI-MedicalImaging\n - **Other Solutions**\n - Compilation - https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection/discussion/193795 by @stanleyjzheng\n - **Notebooks**\n - EDA - https://www.kaggle.com/isaienkov/pulmonary-embolism-detection-eda by @isaienkov\n - Monai 3D CNN Training - https://www.kaggle.com/boliu0/monai-3d-cnn-training by @boliu0\n### Research Papers\n- [Automatic COVID-19 detection from X-ray images using ensemble learning with convolutional neural network](https://link.springer.com/article/10.1007/s10044-021-00970-4)\n- [Automatic detection of COVID-19 infection using chest X-ray images through transfer learning](https://ieeexplore.ieee.org/document/9205687)\n- [CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection](https://ieeexplore.ieee.org/document/9093842)\n- [XCOVNet: Chest X-ray Image Classification for COVID-19 Early Detection Using Convolutional Neural Networks](https://link.springer.com/article/10.1007/s00354-021-00121-7)\n### Discussion Threads\n- Great [summary](https://www.kaggle.com/c/siim-covid19-detection/discussion/239891) of model architectures for Top 3 solutions of similar past competitions by @jesucristo\n- Nice [summary](https://www.kaggle.com/c/siim-covid19-detection/discussion/240015) of key takeaways (includes pre-processing and post-processing techniques as well) from past similar competitions by @mhilmiasyrofi \n- Detailed [explanation](https://www.kaggle.com/c/siim-covid19-detection/discussion/240329) of submission file and labels by @hassiahk \n- An exhaustive [list](https://www.kaggle.com/c/siim-covid19-detection/discussion/240030) of object detection papers and models by @boltcoder ",
"votes": 13
}
],
"comments": [],
"raw_markdown_by_id": {
"1313011": "Placeholder for all the useful resources:\n- Past competitions solutions and notebooks\n- Research papers\n- Discussion threads. \n\nI will be posting more whenever I find something relevant and useful.\n### Competitions\n- [VinBigData Chest X-ray Abnormalities Detection](https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection)\n - **1st Place Solution**\n - Overview - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/231511 by @morizin\n - Journey of one of the team member - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229724 by @fatihozturk\n - Code - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/232393 by @morizin\n - **2nd Place Solution**\n - Overview - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229696 by @zfturbo\n - MMDetection - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229740 by @ivanpan\n - Code - https://github.com/ZFTurbo/2nd-place-solution-for-VinBigData-Chest-X-ray-Abnormalities-Detection\n - **3rd Place Solution**\n - Overview - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229769 by @scusywxy\n - Code - https://github.com/Scu-sen/VinBigData-Chest-X-ray-Abnormalities-Detection\n - **Other Solutions**\n - Compilation - https://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/229628 by @usharengaraju\n - **Notebooks**\n - DICOM to Numpy Array - https://www.kaggle.com/raddar/convert-dicom-to-np-array-the-correct-way by @raddar\n - EDA - https://www.kaggle.com/trungthanhnguyen0502/eda-vinbigdata-chest-x-ray-abnormalities by @trungthanhnguyen0502\n - Visual In-Depth EDA- https://www.kaggle.com/dschettler8845/visual-in-depth-eda-vinbigdata-competition-data by @dschettler8845\n - BBoxes Fusion - https://www.kaggle.com/sreevishnudamodaran/vinbigdata-fusing-bboxes-coco-dataset by @sreevishnudamodaran\n- [RSNA Pneumonia Detection Challenge](https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/)\n - **1st Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/discussion/70421 by @vaillant\n - Code - https://github.com/i-pan/kaggle-rsna18\n - **2nd Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/discussion/70427 by @dmytropoplavskiy\n - Solution based on - https://github.com/yhenon/pytorch-retinanet\n - **3rd Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/discussion/70632 by @pmcheng\n - Code - https://github.com/pmcheng/rsna-pneumonia\n - **Notebooks**\n - EDA - https://www.kaggle.com/peterchang77/exploratory-data-analysis by @peterchang77 and @georges \n - More EDA - https://www.kaggle.com/gpreda/rsna-pneumonia-detection-eda by @gpreda\n - CheXNet - https://www.kaggle.com/ashishpatel26/chexnet-radiologist-level-pneumonia-detection by @ashishpatel26\n- [SIIM-ACR Pneumothorax Segmentation](https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/)\n - **1st Place Solution**\n - Overview - https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/discussion/107824 by @sneddy\n - Code - https://github.com/sneddy/pneumothorax-segmentation\n - **2nd Place Solution**\n - Overview - https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/discussion/108009 by @lanjunyelan\n - Code - https://github.com/yelanlan/Pneumothorax-Segmentation-2nd-place-solution\n - **3rd Place Solution**\n - Overview - https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/discussion/107981 by @bestfitting \n - Code - https://github.com/bestfitting/kaggle/tree/master/siim_acr\n - **Other Solutions**\n - Gold Medal - https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/discussion/108308 by @rohanrao\n - **Notebooks**\n - Starter - https://www.kaggle.com/jesperdramsch/intro-chest-xray-dicom-viz-u-nets-full-data by @jesperdramsch\n - EDA + U-Net - https://www.kaggle.com/ekhtiar/finding-pneumo-part-1-eda-and-unet by @ekhtiar\n- [RSNA STR Pulmonary Embolism Detection](https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection)\n - **1st Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection/discussion/194145 by @wowfattie\n - Code - https://github.com/GuanshuoXu/RSNA-STR-Pulmonary-Embolism-Detection\n - **2nd Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection/discussion/193401 by @vaillant\n - Code - https://github.com/i-pan/kaggle-rsna-pe\n - **3rd Place Solution**\n - Overview - https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection/discussion/193424 by @moewie94\n - Code - https://github.com/moewiee/RSNA2020-Team-VinBDI-MedicalImaging\n - **Other Solutions**\n - Compilation - https://www.kaggle.com/c/rsna-str-pulmonary-embolism-detection/discussion/193795 by @stanleyjzheng\n - **Notebooks**\n - EDA - https://www.kaggle.com/isaienkov/pulmonary-embolism-detection-eda by @isaienkov\n - Monai 3D CNN Training - https://www.kaggle.com/boliu0/monai-3d-cnn-training by @boliu0\n### Research Papers\n- [Automatic COVID-19 detection from X-ray images using ensemble learning with convolutional neural network](https://link.springer.com/article/10.1007/s10044-021-00970-4)\n- [Automatic detection of COVID-19 infection using chest X-ray images through transfer learning](https://ieeexplore.ieee.org/document/9205687)\n- [CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection](https://ieeexplore.ieee.org/document/9093842)\n- [XCOVNet: Chest X-ray Image Classification for COVID-19 Early Detection Using Convolutional Neural Networks](https://link.springer.com/article/10.1007/s00354-021-00121-7)\n### Discussion Threads\n- Great [summary](https://www.kaggle.com/c/siim-covid19-detection/discussion/239891) of model architectures for Top 3 solutions of similar past competitions by @jesucristo\n- Nice [summary](https://www.kaggle.com/c/siim-covid19-detection/discussion/240015) of key takeaways (includes pre-processing and post-processing techniques as well) from past similar competitions by @mhilmiasyrofi \n- Detailed [explanation](https://www.kaggle.com/c/siim-covid19-detection/discussion/240329) of submission file and labels by @hassiahk \n- An exhaustive [list](https://www.kaggle.com/c/siim-covid19-detection/discussion/240030) of object detection papers and models by @boltcoder "
}
}