![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F836513%2F5e9204cda134bba53cf1af56c07f1043%2FEar%20density%20estimation%20from%20high%20resolution%20RGB%20imagery%20using%20deep%20learning%20technique.png?generation=1588625750887065&alt=media\")
DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning [arXiv]\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F836513%2F91b86b32c8ed8611a1515ad1f9f65fd8%2FDeepWheat%20Estimating%20Phenotypic%20Traits%20from%20Crop%20Images%20with%20Deep%20Learning.png?generation=1588625632552117&alt=media\")
TasselNet: Counting maize tassels in the wild via local counts regression network [arXiv]\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F836513%2F564572266ee47615d1ad3c5864a3325a%2FTasselNet%20Counting%20maize%20tassels%20in%20the%20wild%20via%20local%20counts%20regression%20network.png?generation=1588625674313978&alt=media\")
Pheno-Deep Counter : [Researchgate]\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F836513%2F119a79e3776f2835d4372123e9878d39%2FPheno-Deep%20Counter.png?generation=1588625725958523&alt=media\")
More curated list of papers related to plant phenotpying using deep learning and resources are at Awesome deep learning in crop field phenotyping
", "messages": [ { "id": "833484", "postDate": "05/04/2020 21:03:20", "content": "DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning [arXiv]\n
TasselNet: Counting maize tassels in the wild via local counts regression network [arXiv]\n
Pheno-Deep Counter : [Researchgate]\n
More curated list of papers related to plant phenotpying using deep learning and resources are at Awesome deep learning in crop field phenotyping
", "rawMarkdown": "## **Object detection** \n- Ear density estimation from high resolution RGB imagery using deep learning technique [[arXiv]](https://www.researchgate.net/publication/328512173_Ear_density_estimation_from_high_resolution_RGB_imagery_using_deep_learning_technique)\n\n\n### Counting plant/ leaves\n\n- DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning [[arXiv]](https://arxiv.org/abs/1710.00241)\n\n\n- TasselNet: Counting maize tassels in the wild via local counts regression network [[arXiv]](https://arxiv.org/abs/1707.02290)\n\n\n- Pheno-Deep Counter : [[Researchgate]](https://www.researchgate.net/publication/326991923_Pheno-Deep_Counter_a_unified_and_versatile_deep_learning_architecture_for_leaf_counting)\n\n\n\nMore curated list of papers related to plant phenotpying using deep learning and resources are at [Awesome deep learning in crop field phenotyping](https://github.com/simonMadec/awesome-phenotyping-deep-learning)", "votes": null }, { "id": "834244", "postDate": "05/05/2020 12:26:38", "content": "This is really interesting. Thanks for sharing. :)
", "rawMarkdown": "This is really interesting. Thanks for sharing. :)", "votes": null }, { "id": "836497", "postDate": "05/07/2020 03:10:58", "content": "Excellent, thanks for sharing this papers
", "rawMarkdown": "Excellent, thanks for sharing this papers", "votes": null }, { "id": "836651", "postDate": "05/07/2020 06:03:03", "content": "Upvoted 👍 - Thanks for Sharing Fayur
", "rawMarkdown": "Upvoted 👍 - Thanks for Sharing Fayur", "votes": null }, { "id": "837467", "postDate": "05/07/2020 19:34:18", "content": "I don't know if you made the pictures or you copied them but good job bringing them here :)\nNow I want to implement this.
", "rawMarkdown": "I don't know if you made the pictures or you copied them but good job bringing them here :)\nNow I want to implement this.", "votes": null }, { "id": "837471", "postDate": "05/07/2020 19:36:29", "content": "I copied them from papers.
", "rawMarkdown": "I copied them from papers.", "votes": null }, { "id": "837574", "postDate": "05/07/2020 21:49:59", "content": "This seems to be pretty interesting. \nThanks for the links of papers.
", "rawMarkdown": "This seems to be pretty interesting. \nThanks for the links of papers.", "votes": null }, { "id": "841485", "postDate": "05/10/2020 20:12:58", "content": "I'm trying to figure an approach to this. Any ideas for augmenting the data set of wheat ear subobjects.?
", "rawMarkdown": "I'm trying to figure an approach to this. Any ideas for augmenting the data set of wheat ear subobjects.?", "votes": null }, { "id": "841761", "postDate": "05/11/2020 02:24:45", "content": "Interesting
", "rawMarkdown": "Interesting", "votes": null }, { "id": "844761", "postDate": "05/12/2020 20:27:18", "content": "Also go to check the preprint for data description and the bilbio :) : \nhttps://arxiv.org/abs/2005.02162
", "rawMarkdown": "Also go to check the preprint for data description and the bilbio :) : \nhttps://arxiv.org/abs/2005.02162", "votes": null }, { "id": "845758", "postDate": "05/13/2020 12:16:49", "content": "Very much needed for a comprehensive understanding of the details involved in this competition. Much appreciated!
", "rawMarkdown": "Very much needed for a comprehensive understanding of the details involved in this competition. Much appreciated!", "votes": null }, { "id": "845761", "postDate": "05/13/2020 12:19:38", "content": "I would also like to add this paper on Single Shot Detection for reference which is not particularly focused on the plant object detection but might come in handy when dealing with multi box detection scenarios.
", "rawMarkdown": "I would also like to add this [paper](https://arxiv.org/abs/1512.02325) on Single Shot Detection for reference which is not particularly focused on the plant object detection but might come in handy when dealing with multi box detection scenarios.", "votes": null }, { "id": "846877", "postDate": "05/14/2020 03:42:12", "content": "Thank you for sharing the links of papers.
", "rawMarkdown": "Thank you for sharing the links of papers.", "votes": null }, { "id": "879202", "postDate": "06/09/2020 09:39:06", "content": "Such a good share 💯
", "rawMarkdown": "Such a good share 💯", "votes": null }, { "id": "881129", "postDate": "06/10/2020 18:59:18", "content": "Great work!👍
", "rawMarkdown": "Great work!👍", "votes": null } ], "comments": [ { "id": 834244, "author_name": "ipythonx", "author_url": "", "post_date": "05/05/2020 12:26:38", "content": "This is really interesting. Thanks for sharing. :)
", "votes": null, "replies": [] }, { "id": 836497, "author_name": "egiperez", "author_url": "", "post_date": "05/07/2020 03:10:58", "content": "Excellent, thanks for sharing this papers
", "votes": null, "replies": [] }, { "id": 836651, "author_name": "praveengovi", "author_url": "", "post_date": "05/07/2020 06:03:03", "content": "Upvoted 👍 - Thanks for Sharing Fayur
", "votes": null, "replies": [] }, { "id": 837467, "author_name": "alincijov", "author_url": "", "post_date": "05/07/2020 19:34:18", "content": "I don't know if you made the pictures or you copied them but good job bringing them here :)\nNow I want to implement this.
", "votes": null, "replies": [ { "id": 837471, "author_name": "fayzur", "author_url": "", "post_date": "05/07/2020 19:36:29", "content": "I copied them from papers.
", "votes": null, "replies": [] } ] }, { "id": 837574, "author_name": "darshangandhi", "author_url": "", "post_date": "05/07/2020 21:49:59", "content": "This seems to be pretty interesting. \nThanks for the links of papers.
", "votes": null, "replies": [] }, { "id": 841485, "author_name": "raiwills", "author_url": "", "post_date": "05/10/2020 20:12:58", "content": "I'm trying to figure an approach to this. Any ideas for augmenting the data set of wheat ear subobjects.?
", "votes": null, "replies": [] }, { "id": 841761, "author_name": "amithasanshuvo", "author_url": "", "post_date": "05/11/2020 02:24:45", "content": "Interesting
", "votes": null, "replies": [] }, { "id": 844761, "author_name": "simonmadec", "author_url": "", "post_date": "05/12/2020 20:27:18", "content": "Also go to check the preprint for data description and the bilbio :) : \nhttps://arxiv.org/abs/2005.02162
", "votes": null, "replies": [] }, { "id": 845758, "author_name": "siddhantbhambri", "author_url": "", "post_date": "05/13/2020 12:16:49", "content": "Very much needed for a comprehensive understanding of the details involved in this competition. Much appreciated!
", "votes": null, "replies": [] }, { "id": 845761, "author_name": "siddhantbhambri", "author_url": "", "post_date": "05/13/2020 12:19:38", "content": "I would also like to add this paper on Single Shot Detection for reference which is not particularly focused on the plant object detection but might come in handy when dealing with multi box detection scenarios.
", "votes": null, "replies": [] }, { "id": 846877, "author_name": "chaonanxi", "author_url": "", "post_date": "05/14/2020 03:42:12", "content": "Thank you for sharing the links of papers.
", "votes": null, "replies": [] }, { "id": 879202, "author_name": "dasmehdixtr", "author_url": "", "post_date": "06/09/2020 09:39:06", "content": "Such a good share 💯
", "votes": null, "replies": [] }, { "id": 881129, "author_name": "pratikbarua", "author_url": "", "post_date": "06/10/2020 18:59:18", "content": "Great work!👍
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "833484": "## **Object detection** \n- Ear density estimation from high resolution RGB imagery using deep learning technique [[arXiv]](https://www.researchgate.net/publication/328512173_Ear_density_estimation_from_high_resolution_RGB_imagery_using_deep_learning_technique)\n\n\n### Counting plant/ leaves\n\n- DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning [[arXiv]](https://arxiv.org/abs/1710.00241)\n\n\n- TasselNet: Counting maize tassels in the wild via local counts regression network [[arXiv]](https://arxiv.org/abs/1707.02290)\n\n\n- Pheno-Deep Counter : [[Researchgate]](https://www.researchgate.net/publication/326991923_Pheno-Deep_Counter_a_unified_and_versatile_deep_learning_architecture_for_leaf_counting)\n\n\n\nMore curated list of papers related to plant phenotpying using deep learning and resources are at [Awesome deep learning in crop field phenotyping](https://github.com/simonMadec/awesome-phenotyping-deep-learning)", "834244": "This is really interesting. Thanks for sharing. :)", "836497": "Excellent, thanks for sharing this papers", "836651": "Upvoted 👍 - Thanks for Sharing Fayur", "837467": "I don't know if you made the pictures or you copied them but good job bringing them here :)\nNow I want to implement this.", "837471": "I copied them from papers.", "837574": "This seems to be pretty interesting. \nThanks for the links of papers.", "841485": "I'm trying to figure an approach to this. Any ideas for augmenting the data set of wheat ear subobjects.?", "841761": "Interesting", "844761": "Also go to check the preprint for data description and the bilbio :) : \nhttps://arxiv.org/abs/2005.02162", "845758": "Very much needed for a comprehensive understanding of the details involved in this competition. Much appreciated!", "845761": "I would also like to add this [paper](https://arxiv.org/abs/1512.02325) on Single Shot Detection for reference which is not particularly focused on the plant object detection but might come in handy when dealing with multi box detection scenarios.", "846877": "Thank you for sharing the links of papers.", "879202": "Such a good share 💯", "881129": "Great work!👍" }, "source": "meta" }