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Jan 7, 2021 · In this paper, we present our work on developing a 3D extension of the ResNet architecture to distinguish between two build orientations of tensile bars ...
Dec 22, 2020 · In this paper, we report on the application of a three-dimensional exten- sion of a residual convolutional neural network architecture (ResNet [ ...
In this paper, we present our work on developing a 3D extension of the ResNet architecture to distinguish between two build orientations of tensile bars ...
This paper presents work on developing a 3D extension of the ResNet architecture to distinguish between two build orientations of tensile bars produced by ...
In this paper, we present our work on developing a 3D extension of the ResNet architecture to distinguish between two build orientations of tensile bars ...
We present our work on developing a 3D extension of the ResNet architecture to distinguish between two build orientations of tensile bars produced by AM.
In this paper, we present our work on developing a 3D extension of the ResNet architecture to distinguish between two build orientations of tensile bars ...
CNNs learn by representing feature detecting convolutions with kernels (a 3D tensor) weights, and these weights can be modified through gradient descent methods ...
In this work, we show that convolutional neural networks (CNN), a machine learning algorithm, can directly predict the energy required to compressively deform ...
Missing: orientation | Show results with:orientation
A convolutional neural network (CNN) is developed that, starting from the tridimensional representation of an object, predicts the rotation angle pair that ...