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-training and model merging/fusion; (c) establish secure, scalable and efficient infrastructure for data management, distributed training, model evaluation, deployment and continuous improvement
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on application logic rather than underlying algorithm development), and the capability of independently driving the full "Data-AI-Deployment" process; (c) the ability to evaluate the fit between AI applications
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on application logic rather than underlying algorithm development), and the capability of independently driving the full "Data-AI-Deployment" process; (c) the ability to evaluate the fit between AI applications
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challenge issues, using advanced machine learning models and necessary techniques; (d) evaluate and validate the performance of proposed methods and algorithms through theoretical analysis; (e) maintain
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analysis; (b) develop and implement algorithms for 3D perception (e.g. segmentation, localization and mapping); (c) design and execute experiments to evaluate, validate and refine algorithms and