Hey Kagglers,
\nThe ALASKA2 Image Steganalysis Competition has closed! We hope you were able to learn a lot, and use your machine learning skills on this unique twist on a computer vision problem.
\nThis year’s competition ended with 1,322 participants on 1,095 teams! We had 20,918 submissions from 66 countries! For 156 users (including 3 in the top 10!), this was their first competition. We also had 1 new Grandmaster at the conclusion of the competition and a brand new overall top ranked Kaggle Competitions Grandmaster (Congrats Guanshuo)! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!
We were excited to work with Remi Cogranne for the second iteration of this competition and the Troyes University of Technology. We're glad they choose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future.
\nWe're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.
\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact compliance. Please fill in all the fields honestly.
\nThe top potential winning teams have been contacted via email to provide their winning solutions for host review. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams.
\nYou should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.
\nIn the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top kernels, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.
\nHappy Modeling!
\nKaggle Team
Hey Kagglers,
\nThe ALASKA2 Image Steganalysis Competition has closed! We hope you were able to learn a lot, and use your machine learning skills on this unique twist on a computer vision problem.
\nThis year’s competition ended with 1,322 participants on 1,095 teams! We had 20,918 submissions from 66 countries! For 156 users (including 3 in the top 10!), this was their first competition. We also had 1 new Grandmaster at the conclusion of the competition and a brand new overall top ranked Kaggle Competitions Grandmaster (Congrats Guanshuo)! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!
We were excited to work with Remi Cogranne for the second iteration of this competition and the Troyes University of Technology. We're glad they choose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future.
\nWe're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.
\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact compliance. Please fill in all the fields honestly.
\nThe top potential winning teams have been contacted via email to provide their winning solutions for host review. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams.
\nYou should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.
\nIn the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top kernels, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.
\nHappy Modeling!
\nKaggle Team
Congratulations to all the participants!
", "rawMarkdown": "Congratulations to all the participants!", "votes": 1 }, { "id": 950038, "postDate": "2020-07-29T06:24:57.640Z", "rawMarkdown": "", "isDeleted": true }, { "id": 949987, "postDate": "2020-07-29T05:29:31.350Z", "rawMarkdown": "", "isDeleted": true } ], "comments": [ { "id": 950700, "author_name": "Alin Cijov", "author_url": "", "post_date": "2020-07-29T14:57:58.730000", "content": "Congratulations to all the participants!
", "votes": 1, "replies": [] }, { "id": 950038, "author_name": "", "author_url": "", "post_date": "2020-07-29T06:24:57.640000", "content": "", "votes": 0, "replies": [] }, { "id": 949987, "author_name": "", "author_url": "", "post_date": "2020-07-29T05:29:31.350000", "content": "", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "949483": "Hey Kagglers,\n\nThe ALASKA2 Image Steganalysis Competition has closed! We hope you were able to learn a lot, and use your machine learning skills on this unique twist on a computer vision problem. \nThis year’s competition ended with 1,322 participants on 1,095 teams! We had 20,918 submissions from 66 countries! For 156 users (including 3 in the top 10!), this was their first competition. We also had 1 new Grandmaster at the conclusion of the competition and a brand new overall top ranked Kaggle Competitions Grandmaster (Congrats [Guanshuo](https://www.kaggle.com/wowfattie))! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking! \n\nWe were excited to work with [Remi Cogranne](https://www.kaggle.com/remicogranne) for the second iteration of this competition and the Troyes University of Technology. We're glad they choose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future. \n\nWe're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.\n\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact [compliance](https://www.kaggle.com/compliance). Please fill in all the fields honestly.\n\nThe top potential winning teams have been contacted via email to provide their winning solutions for host review. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams.\n\nYou should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.\n\nIn the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top kernels, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.\n\nHappy Modeling!\nKaggle Team\n\n###Top Solutions\n- [1st Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168548)\n- [2nd Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168546)\n- [3rd Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168870)\n- [4th Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168537)\n- [8th Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168519)\n- [9th Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168608)\n- [12th Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168507)\n- [13th Place Solution pt 1](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168510)\n- [13th Place Solution pt 2](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168542)\n- [14th Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168611)\n- [18th Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168771)\n- [31st Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168509)\n- [34th Place Solution](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/168702)\n\n###Top Notebooks\n- [Steganalysis Complete Understanding and Model](https://www.kaggle.com/tanulsingh077/steganalysis-complete-understanding-and-model)\n- [GPU Baseline](https://www.kaggle.com/shonenkov/train-inference-gpu-baseline)\n- [All You Need to Know](https://www.kaggle.com/prashant111/alaska2-image-steganalysis-all-you-need-to-know)\n- [Multiclass PyTorch EffNet2](https://www.kaggle.com/andradaolteanu/alaska2-competition-multiclass-pytorch-effnetb2)\n- [CNN Multiclass Classifier](https://www.kaggle.com/meaninglesslives/alaska2-cnn-multiclass-classifier)\n- [EfficientNet on TPUs](https://www.kaggle.com/xhlulu/alaska2-efficientnet-on-tpus)\n\n###Other Top Discussions\n- [A few tips for easy start](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/155392)\n- [Alaska2: Intro + Literature Review + External Data + Networks + Relevant Githubs](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/146622)\n- [Paper worth Mentioning](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/146610)\n- [Impact of steganography: do not look only at pixel difference](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/147494)\n- [Best Single Model](https://www.kaggle.com/c/alaska2-image-steganalysis/discussion/148162)\n", "950700": "Congratulations to all the participants!", "950038": "", "949987": "" } }