Recent advances and future trends in Artificial Intelligence (AI)-based methods for biomedical imaging are discussed in this work. Among them, a focus is given on the "three-steps" learning-by-Examples (3-LB...
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ISBN:
(纸本)9798350390797;9789532901351
Recent advances and future trends in Artificial Intelligence (AI)-based methods for biomedical imaging are discussed in this work. Among them, a focus is given on the "three-steps" learning-by-Examples (3-LBE) paradigm which allows the efficient/effective generation of robust and accurate surrogate models (SMs) for the real-time inversion of electromagnetic (EM) data. Moreover, the pillar ideas and concepts of the System-by-Design (SbD) framework are outlined when addressing the solution of complex inverse scattering problems (ISPs) arising in several biomedical microwave imaging scenarios.
Following the great success of curriculum learning in the area of machinelearning, a novel deep curriculum learning method proposed in this paper, entitled DCL, particularly for the classification of fully polarimetr...
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Managing diabetes effectively requires accurate monitoring of blood glucose levels. Traditional invasive methods for such monitoring can be cumbersome and uncomfortable for patients. This study introduces a non-invasi...
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In electric vehicles (EVs), lithium-ion batteries playa vital role;determining how long they will be useful is essential to ensuring their stability, longevity, and safety. In the subject of battery health management,...
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Heart disease detection is done here using a number of sample data taken from various sources. We have to use different machinelearning technique to detect whether a given data is cancer infected or not. An ingenious...
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This document introduces the basic concepts of Artificial Intelligence (AI) and machinelearning (ML), and some typical applications are mentioned;It also describes some of the most used AI platforms to develop projec...
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ISBN:
(纸本)9798350398960
This document introduces the basic concepts of Artificial Intelligence (AI) and machinelearning (ML), and some typical applications are mentioned;It also describes some of the most used AI platforms to develop projects using ML algorithms. Specifically, the implementation of machinelearning solutions is addressed using the MediaPipe framework developed by Google. MediaPipe uses pre-trained models in TensorFlow, OpenCV to manipulate video, and FFmpeg to handle audio data;in addition, it is available for Android, iOS, C++, Python, and JavaScript.
Diffusion models have demonstrated their powerful generative capability in many tasks, with great potential to serve as a paradigm for offline reinforcement learning. However, the quality of the diffusion model is lim...
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Diffusion models have demonstrated their powerful generative capability in many tasks, with great potential to serve as a paradigm for offline reinforcement learning. However, the quality of the diffusion model is limited by the insufficient diversity of training data, which hinders the performance of planning and the generalizability to new tasks. This paper introduces AdaptDiffuser, an evolutionary planning method with diffusion that can self-evolve to improve the diffusion model hence a better planner, not only for seen tasks but can also adapt to unseen tasks. AdaptDiffuser enables the generation of rich synthetic expert data for goal-conditioned tasks using guidance from reward gradients. It then selects high-quality data via a discriminator to finetune the diffusion model, which improves the generalization ability to unseen tasks. Empirical experiments on two benchmark environments and two carefully designed unseen tasks in KUKA industrial robot arm and Maze2D environments demonstrate the effectiveness of AdaptDiffuser. For example, AdaptDiffuser not only outperforms the previous art Diffuser (Janner et al., 2022) by 20.8% on Maze2D and 7.5% on MuJoCo locomotion, but also adapts better to new tasks, e.g., KUKA pick-and-place, by 27.9% without requiring additional expert data. More visualization results and demo videos could be found on our project page.
This paper addresses the widespread impact of machinelearning on diverse industries and the current high learning threshold in designing and training models. It proposes a no-code, data-driven tool for multidimension...
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machinelearning is a widely popular field that is being used in an increasingly large number of projects worldwide. This necessitates the use of certain practices to create a structured framework for such projects. T...
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Breast Cancer is considered to be very severe in women but mortality rate of cancer can be minimized by early diagnosis and screening of cancer. The timely identification of cancer at initial stage can enhance the sur...
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