Difference between revisions of "Machine Learning"
From Living Building Science
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Welcome to the Machine Learning Team Page! One of our past goals last semester was to create a bee recognition and classification project to complement our finished flower recognition model and eventually integrate both of these models with the bee classification project of the previous ML team as well as the BeeKeeper GO app. Once successfully integrated, our models could potentially be used to enhance the experience of the app and make it more educational for users, as the classification/identification of flowers will allow users to learn while taking pictures. In addition, another goal of last semester was to use data analysis and computer vision to detect the occurrence of swarms in bee hives and the contributing factors/warning signs that will lead to a swarm occurring. Our current goals include improving and expanding our past projects as well as potentially creating machine learning and analysis tools to assist the other sub-teams in Living Building Science with their goals. | Welcome to the Machine Learning Team Page! One of our past goals last semester was to create a bee recognition and classification project to complement our finished flower recognition model and eventually integrate both of these models with the bee classification project of the previous ML team as well as the BeeKeeper GO app. Once successfully integrated, our models could potentially be used to enhance the experience of the app and make it more educational for users, as the classification/identification of flowers will allow users to learn while taking pictures. In addition, another goal of last semester was to use data analysis and computer vision to detect the occurrence of swarms in bee hives and the contributing factors/warning signs that will lead to a swarm occurring. Our current goals include improving and expanding our past projects as well as potentially creating machine learning and analysis tools to assist the other sub-teams in Living Building Science with their goals. | ||
| + | === Past Semester Projects === | ||
| + | [https://drive.google.com/file/d/1bFO8l0xRe4-gTViQ_ZZhRQrpBxUXFIB_/view?usp=sharing Fall 2020 Semester Poster] | ||
| + | [https://drive.google.com/file/d/13J5NKL8clxtGbLXqypOgU7qk6ZIvZxSE/view?usp=sharing Spring 2020 Semester Poster] | ||
Revision as of 15:25, 5 February 2021
Welcome to the Machine Learning Team Page! One of our past goals last semester was to create a bee recognition and classification project to complement our finished flower recognition model and eventually integrate both of these models with the bee classification project of the previous ML team as well as the BeeKeeper GO app. Once successfully integrated, our models could potentially be used to enhance the experience of the app and make it more educational for users, as the classification/identification of flowers will allow users to learn while taking pictures. In addition, another goal of last semester was to use data analysis and computer vision to detect the occurrence of swarms in bee hives and the contributing factors/warning signs that will lead to a swarm occurring. Our current goals include improving and expanding our past projects as well as potentially creating machine learning and analysis tools to assist the other sub-teams in Living Building Science with their goals.