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      "content": "Bali26 (https://realtechsupport.org/projects/bali26_overview_bahasa.html) is an image dataset dedicated to ethnobotany, the study of the interaction between people and plants. Bali26 is the first machine-vision ready image collection of ethnobotanically significant flora of south-east Asia, collected on the island of Bali in 2020 (and amended in 2021) together with Balinese residents with intimate local knowledge in coordination with expertise from the Indonesia National Research and Innovation Agency.\n\nThe images were created from video documentation of flora in the wild with Catch & Release (https://github.com/realtechsupport/c-plus-r). The images show a deliriously rich flora with more information content (entropy) than similar examples in ImageNet. Not unlike the IRIS dataset, the data samples of Bali26 were collected in a controlled real-world environment; in the wild, in a restricted area, within a short time frame, by a small group of data collectors. Bali26 contains 26 categories with approximately 2000 images per category. \n\nThe publications listed below describe the curation of this dataset and some early classification experiments.\n\n·         M. Böhlen and W. Sujarwo, \"Return to Bali,\" 2020 Second International Conference on Transdisciplinary AI (TransAI), 2020, pp. 92-95.\n\n·         M. Böhlen and W. Sujarwo, \"Machine Learning in Ethnobotany,\" 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020, pp. 108-113.\n\n·         M. Böhlen, R. Jain, W. Sujarwo and V. Chandola, \"From images in the wild to video-informed image classification,\" 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021, pp. 656-661.\n\n\n## Files\n\n*   **bali-26_train** - the training set, which includes 26 folders, each contains images of the same category\n*   **bali-26_test** - the test set, which includes test images without folder structures\n*   **sample_submission.csv** - a sample submission file in the correct format\n",
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      "name": "Description",
      "content": "We are pleased to cordially invite university students, who consider Data Science and related fields their careers, to attend the 3rd International Competition in Data Science & Artificial Intelligence, organized by The International Society of Data Scientists. Students graduated within 5 years are eligible to attend. Each team can optionally have an advisor, who may be a professor or a data science professional. The competition is to create a playground for young Data Scientists to grow skills, knowledge, experience, and collaboration for their career path. The competition committee includes professors and industry leaders around the world.\n\nProfessor Marc Böhlen has collected a machine-vision ready image collection of ethnobotanically significant flora of south-east Asia on the island of Bali in 2020 - 2021 together with Balinese residents with intimate local knowledge in coordination with expertise from the Indonesia National Research and Innovation Agency. He is willing to provide the data to the competition, and curious to see if you can take the challenge.\n\nWill you be able to recognize these plants using machine learning and deep learning skills? Your team will submit the result for evaluation at the end of the competition.\n\nThe committee chairs of this competition track include:\nDr. Shaima Ali, Assistant Professor (Software Engineering), Electrical and Computer Engineering Department, Western University (Canada)\nMarc Böhlen, Professor, Department of ART, Emerging Practices in Computational Media, University at Buffalo, New York, USA\nDr. Quang Hieu Vu, Head of Data Platform at ZaloPay\nDr. Christopher Do, ISODS President\nDr. Nam Nguyen, ISODS Vice President\nMr. Cory Wang, ISODS Vice President\n\n## About - The International Society of Data Scientists\n\nThe International Society of Data Scientists (or The ISODS), at www.isods.org, registered as a Massachusetts non-profit, is a professional organization for Data Science and AI practitioners and researchers, which may include Data Scientists, Machine Learning Scientists, AI Scientists, Data Analysts, Data Engineers, Software Engineers, Risk Analysts, Actuaries, Business Analysts, and more, who apply Data Science and AI at work. ISODS promotes Data Science and AI domestically in the United States as well as internationally via professional exams, competitions, conferences, training, and publications.\n\n## Acknowledgements\n\nWe thank Professor Marc Böhlen, Department of ART, Emerging Practices in Computational Media, University at Buffalo, New York, USA for providing this dataset.\n\nWe thank [Professors and Industry Leaders](https://www.isods.org/news-times/item/27-competition-committee-for-the-3rd-annual-international-data-science-ai-competition-for-the-year-2022) who volunteer to participate and contribute in the competition committee.\n",
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      "name": "Evaluation",
      "content": "The evaluation metric for this competition is accuracy.\n\n## Submission Format\n\nSubmission files  (*.csv) should contain two columns: `id` and `class`. `class` is the labels of the test dataset predicted by the model.\n\nThe file should contain a header and have the following format:\n```\nid, class\n1.jpg,bamboo\n2.jpg,mango\n3.jpg,mango\n```",
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      "name": "rules",
      "content": "Rules include the following\n - Don't cheat!\n - Apply yourself!\n - Have fun!\n\nAfter the competition deadline, participating teams should be able to make their notebooks public. In the notebook, students can provide more information about their team, such as university names and locations, advisor (if applicable), etc.",
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      "name": "What To Earn",
      "content": "The competition is to provide experience to young data scientists, who are students. We do not offer cash prizes according to Kaggle's rules. Instead, top performers will be selected to submit their reports as conference papers in the related conference by ISODS, and considered passing the ISODS Deep Learning 1 (DL1) exam if using the relevant approaches. Paper authors may choose to make the paper more interesting by considering this[ extra data](https://u.pcloud.link/publink/show?code=XZUqGVVZJ9lI5NUfTXSOQ8Qfoz5KVLJNT79y) in which there are more than one plant in each image.\n\n`The ISODS provides professional exams toward several designations of the Society, including Associate Master (CM), Fellow Master (FM), and Grandmaster (GM). These titles are not related to similar titles by Kaggle.`",
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      "name": "Timeline",
      "content": "Start Date - March 28, 2022\n\nEntry Deadline - Same as the Final Submission Deadline.\n\nTeam Merger Deadline - Same as the Final Submission Deadline.\n\nFinal Submission Deadline - June 19, 2022\n\nAll deadlines are at 11:59 PM UTC on the corresponding day unless otherwise noted. The competition organizers reserve the right to update the contest timeline if they deem it necessary.",
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      "name": "All The Tracks",
      "content": "All Kaggle-based Community Competition Tracks are:\n\n1> Company Bankruptcy Prediction\nhttps://www.kaggle.com/c/company-bankruptcy-prediction\n\n2> Classification of plants of Southeast Asia\nhttps://www.kaggle.com/c/classification-of-plants-of-southeast-asia\n\n3> Fashion and Beauty Review Classification\nhttps://www.kaggle.com/competitions/fashion-and-beauty-review-classification/\n\nThere is no limitation in term of the number of tracks a team or individual can participate.\n\nTop performers will be selected to submit their reports as conference papers in the related conference by ISODS. \n\nTop performers in track 1 are considered passing the ISODS Machine Learning exam; in track 2 as passing the Deep Learning 1 (DL1) exam; in track 3 as passing the Deep Learning 2 (DL2) exam. See more about ISODS Professional Exams organized by the International Institute of Data Science and Artificial Intelligence at ISODS website (https://www.isods.org)",
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      "name": "Committee",
      "content": "The [competition committee composition](https://www.isods.org/item/27-competition-committee-for-the-3rd-annual-international-data-science-ai-competition-for-the-year-2022) is as follows:\n\nDr. Krishna R. Pattipati, Board of Trustees Distinguished Professor & UTC Professor in Systems Engineering, Department of Electrical and Computer Engineering, University of Connecticut, Connecticut, USA\n\nDr. Rajakumar Arul, Assistant Professor, School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology (VIT) Chennai Campus, India\n\nMarc Böhlen, Professor, Department of ART, Emerging Practices in Computational Media, University at Buffalo, New York, USA\n\nDr. Mohammad Soltanieh-ha, Assistant Professor, Questrom School of Business, Boston University, Massachusetts, USA\n\nDr. Manar Alalfi, Associate Professor in Software Engineering, Ryerson University, Toronto, Ontario M5B 2K3, Canada; Adjunct Assistant Professor, Queen's University School of Computing, Kingston, Ontario K7L 3N6, Canada\n\nDr. Sebastian Tomczak, Department of Operations Research and Business Intelligence, Faculty of Management, Wroclaw University of Science and Technology, Wrocław, Poland\n\nDr. Shaimaa Ali, Assistant Professor (Software Engineering) at the Electrical and Computer Engineering Department, Western University, London, Ontario N6A 3K7, Canada\n\nDr. Renzhi Cao, Assistant Professor, Department of Computer Science, Pacific Lutheran University, Washington, USA\n\nDr. Adisak Sukul, Associate Teaching Professor at Department of Computer Science, Iowa State University, Iowa, USA\n\nDr. Haiyang Kong, Assistant Professor, Business School of Beijing Normal University, Beijing, China\n\nDr. Nguyet Nguyen, Associate Professor, Youngstown State University, Ohio, USA\n\nDr. Hoa Trung Dinh, Assistant Professor, Troy University, Alabama, USA\n\nDr. Kim Phuc Tran, Associate Professor, University of Lille, Lille, France\n\nDr. Lan Vu, Professor, Department Head and Chair at Hanoi University of Public Health, Vietnam\n\nDr. Duy Nguyen, Assistant Professor, Marist College, New York, USA\n\nDr. Hoan Nguyen, Computer Scientist, Jackson Lab, Connecticut, USA\n\nDr. Bay Dinh Vo, Associate Professor, HUTECH University of Technology, Vietnam\n\nDr. Son P Nguyen, Lecturer at University of Economics and Law, Vietnam\n\nDr. Vinh Dang, Lecturer, Information Technology Faculty, Industrial University of HCM City, Vietnam\n\nDr. Gia Nhu Nguyen, Associate Professor & Dean of School of Computer Science, Duy Tan University, Vietnam\n\nDr. Bao The Pham, Associate Professor at Saigon University, Vietnam\n\nDr. Loan Nguyen, Associate Professor at International University, Vietnam\n\nDr. Christopher Do, ISODS President, Massachusetts, USA\n\nDr. Nam Nguyen, ISODS Vice President and Staff Data Scientist at Wayfair, Texas, USA\n\nMr. Cory Wang, ISODS Vice President, Connecticut, USA\n\nDr. Phu Vu, Regional Research Director, WorldQuant, Vietnam\n\nDr. Quang Hieu Vu, Head of Data Platform, ZaloPay\n\nDr. Nam Thanh Nguyen, FUNiX Founder, Former FPT CEO\n\nDr. Jianmo Ni, Software Engineer, Google\n\nISODS thanks to all the voluntary work by committee members, and looks forward to the participation and contribution. We would like to thank all the authors who contributed their datasets to the competition tracks as well. ",
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    {
      "name": "Other Credits",
      "content": "We would like to thank Addison Howard and Laurie White at Google, who help during the setting-up phase. ",
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    {
      "name": "Paper Template",
      "content": "If your team is invited to submit a conference paper, [download the paper template PDSAI_Template.docx here](https://github.com/isods/templates)",
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