• Geodesic Convolutional Shape Optimization🔍
• Separability and geometry of object manifolds in deep neural networks🔍
• A generalized approach for automatic 3|D geometry assessment of ...🔍
• Medical Image Analysis using Convolutional Neural Networks🔍
• Application of convolutional neural networks in medical images🔍
• High|fidelity geometry generation from CT data using convolutional ...🔍
• Review of deep learning🔍
• is geometric deep learning for real or is it a small group of people ...🔍

Geodesic Convolutional Shape Optimization - Neural Concept

Geodesic Convolutional Neural Networks are designed to handle this kind of data by incorporating the geometric information of the input data ...

Separability and geometry of object manifolds in deep neural networks

6a, bottom), consistent with the expected ability of this convolution layer to average out substantial variability in images due to translation.

A generalized approach for automatic 3-D geometry assessment of ...

Automatic segmentation of vessels in the transverse view suffers from the low lateral resolution and contrast. Convolutional neural networks are a promising ...

Medical Image Analysis using Convolutional Neural Networks

An intermodal dataset having five modalities and twenty-four classes are used to train the network for the purpose of classification. Three ...

Application of convolutional neural networks in medical images

The tasks of CNNs in the field of medical imaging mainly include disease classification and grading (13), localization and detection of pathological targets (14) ...

High-fidelity geometry generation from CT data using convolutional ...

A convolutional neural network (CNN) coupled with a tailored loss function is implemented to achieve state-of-the-art accuracy in surface ...

Review of deep learning: concepts, CNN architectures, challenges ...

Convolutional neural network (CNN) is one of the most popular and used of DL networks [19, 20]. Because of CNN, DL is very popular nowadays. The ...

is geometric deep learning for real or is it a small group of people ...

Geometric deep learning is based on group theory. The input of the neural networks, usually in the euclidean space, is transformer into a SO(3) ...

Deep learning for geometric and semantic tasks in photogrammetry ...

Figure 4. Architecture of a typical Convolutional Neural Network for image analysis. The figure shows the successive steps of convolution and pooling to ...

Geometric property-based convolutional neural network for indoor ...

In this article, we focus on region-based convolutional neural network (CNN) detector and propose a geometric property-based Faster R-CNN method (GP-Faster) ...

Towards Geometric Deep Learning - The Gradient

It provides a common blueprint allowing to derive from first principles neural network architectures as diverse as CNNs, GNNs, and Transformers.

Convolutional Neural Networks on Surfaces via Seamless Toric ...

A recent research e ort in the geometry processing and vision com- munities is to translate the incredible success of deep convolutional neural networks (CNN) ...

Past, Present, And Future, by Michael Bronstein - YouTube

Seminar by Michael Bronstein at the UCL Centre for AI. Recorded on the 3rd February 2021. Abstract Geometric deep learning has recently ...

Convolutional neural network - Wikipedia

CNNs use relatively little pre-processing compared to other image classification algorithms. This means that the network learns to optimize the filters (or ...

"Geometric Deep Learning: The Erlangen Programme of ML" - M ...

Geometric Deep Learning: The Erlangen ... Deep learning on graphs: successes, challenges | Graph Neural Networks | Michael Bronstein.

CT slice alignment to whole-body reference geometry by ...

Request PDF | CT slice alignment to whole-body reference geometry by convolutional neural network | Volumetric medical imaging lacks a standardised ...

Neural Networks - (Discrete Geometry) - Vocab, Definition ... - Fiveable

For example, convolutional neural networks (CNNs) excel at image recognition ... In healthcare, for instance, neural networks assist in diagnostic processes by ...

VGG-16 | CNN model - GeeksforGeeks

It consists of multiple layers, including convolutional, pooling, and fully connected layers. CNNs are highly effective for tasks like image ...

Geometric deep optical sensing - Science

... medical imaging, environmental monitoring, infrared astronomy ... the roles of classical and quantum geometry and deep neural networks.

CT slice alignment to whole-body reference geometry by ... - ProQuest

Subsequently, a convolutional neural network is trained to associate axial slice CT image appearance with the standardised coordinate value along the patient ...