Results 31 to 40 of about 1,166,366 (314)
Denoising Diffusion Probabilistic Models and Transfer Learning for citrus disease diagnosis
Frontiers in Plant Science, 2023 ProblemsPlant Disease diagnosis based on deep learning mechanisms has been extensively studied and applied. However, the complex and dynamic agricultural growth environment results in significant variations in the distribution of state samples, and the ...
Yuchen Li +4 more
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Reinforcement Learning in an Environment Synthetically Augmented with Digital Pheromones [PDF]
Advances in Artificial Intelligence, 2014 Reinforcement learning requires information about states, actions, and outcomes as the basis for learning. For many applications, it can be difficult to construct a representative model of the environment, either due to lack of required information or because of that the model's state space may become too large to allow a solution in a reasonable ...
Salvador E. Barbosa, Mikel D. Petty
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Producing Synthetic Dataset for Human Fall Detection in AR/VR Environments
Applied Sciences, 2021 Human poses and the behaviour estimation for different activities in (virtual reality/augmented reality) VR/AR could have numerous beneficial applications.
Denis Zherdev +5 more
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Student driven learning in Synthetic Environments
Procedia CIRP, 2019 113 master students of multiple engineering study backgrounds were challenged to develop solutions for the Fraunhofer Project Center at the University of Twente (FPC@UT). In 20 groups the students had to develop a synthetic environment to monitor, manage and control a pilot plant or virtual factory.
Damgrave, R.G.J., Lutters, E.
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Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation [PDF]
Small Methods, 2020 Nanoparticles occur in various environments as a consequence of man-made processes, which raises concerns about their impact on the environment and human health.
L. Mill +14 more
semanticscholar +1 more source
Nature Communications, 2023 Accurate prediction of reactivity and selectivity provides the desired guideline for synthetic development. Due to the high-dimensional relationship between molecular structure and synthetic function, it is challenging to achieve the predictive modelling
Shu-Wen Li +4 more
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Synthetic environment for machine learning experiments
, 2022 This thesis addresses the problem of data scarcity in human deep-learning applications. Automated estimation of human shape and pose from an image is challenging. It is even more difficult to map the identified human pixels onto a 3D model. Existing deep-learning models learn to map manually labelled human pixels in 2D images onto human surface, which ...
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A deep learning approach to detecting volcano deformation from satellite imagery using synthetic datasets [PDF]
Remote Sensing of Environment, 2019 Satellites enable widespread, regional or global surveillance of volcanoes and can provide the first indication of volcanic unrest or eruption. Here we consider Interferometric Synthetic Aperture Radar (InSAR), which can be employed to detect surface ...
N. Anantrasirichai +3 more
semanticscholar +1 more source
Computational Intelligence and Neuroscience, 2021 Recently, Internet of Things (IoT) and cloud computing environments become commonly employed in several healthcare applications by the integration of monitoring things such as sensors and medical gadgets for observing remote patients.
Suliman A. Alsuhibany +6 more
semanticscholar +1 more source
Sensors, 2022 Structural health monitoring systems that employ vision data are under constant development. Generating synthetic vision data is an actual issue. It allows, for example, for obtention of additional data for machine learning techniques or predicting the ...
Paweł Zdziebko +2 more
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