This study proposes a self-supervised method to reconstruct 3D limbic structures from 2D landmarks extracted single view. The loss of self-consistency can be reduced by performing random orthogonal projection the reconstructed structure. Thus, training process using geometric in reconstruction–projection–reconstruction process. network mainly consists graph convolution and Transformer encoders....

Endothelial progenitor cell (EPC) transplantation induces the formation of new blood-vessel networks to supply nutrients and oxygen, and is feasible for the treatment of ischemia and cardiovascular diseases. However, the role of EPCs as a source of proangiogenic cytokines and consequent generators of an extracellular growth factor microenvironment in three-dimensional (3D) microvessel formation...

Recently, the search for an axion insulator state in ferromagnet-3D topological (TI) heterostructure and $\mathrm{MnBi_2Te_4}$ has attracted intensive interest. However, its detection remains difficult experiments. We systematically investigate disorder-induced phase transition of a 3D TI with antiparallel magnetization alignment surfaces. It is found that there exists 2D which shares same univ...

3D shape models that directly classify objects from 3D information have become more widely implementable. Current state of the art models rely on deep convolutional and inception models that are resource intensive. Residual neural networks have been demonstrated to be easier to optimize and do not suffer from vanishing/exploding gradients observed in deep networks. Here we implement a residual ...

The 3D convolutional neural network (CNN) is able to make full use of the spatial 3D context information of lung nodules, and the multi-view strategy has been shown to be useful for improving the performance of 2D CNN in classifying lung nodules. In this paper, we explore the classification of lung nodules using the 3D multi-view convolutional neural networks (MV-CNN) with both chain architectu...

Security of data is of prime importance. Security is a very complex and vast topic. One of the common ways to protect this digital data from unauthorized eavesdropping is encryption. This paper introduces an improved image encryption technique based on a chaotic 3D cat map and Turing machine in the form of dynamic random growth technique. The algorithm consists of two main sections: The first d...

Nowadays, System-on-Chips (SoCs) designers are forced to integrate tens to hundreds of functional and storage blocks in a single die to implement emerging complex computation, multimedia and network services. The integration of huge degree of the blocks in a single die poses new challenge in designing the interconnect architecture of the blocks in SoCs. The traditional bus based interconnect in...

This paper presents a novel method for face alignment under unknown head poses and nonrigid warp, within the framework of markov random field. The proposed method learns a 3D face shape model comprised of 31 facial features and a texture model for each facial feature from a 3D face database. The models are combined to serve as the unary, pairwise and high order constraints of the markov random ...

Zusammenfassung: Der vorliegende Beitrag stellt zuerst ein Verfahren vor, welches das simultane Messen mit mehreren, gleichartigen Ultraschallsensoren erlaubt. Dazu werden auf realen Messungen basierende, experimentelle Ergebnisse präsentiert. Anschließend wird beschrieben, wie dieses Verfahren prinzipiell zur ultraschallbasierten 3D-Entfernungsmessung genutzt werden kann dabei auftretende Prob...

This paper presents a formal model of an active recognition system that can be programmed by learning. At each time step the system decides between producing an action to generate new data and stopping to issue the name of the object observed. The actions can be directed either towards the external environment or towards the internal perceptual system of the agent. The decision strategy is base...