The need for CT scan analysis is growing for pre-diagnosis and therapy of abdominal organs. Automatic organ segmentation of abdominal CT scan can help radiologists analyze the scans faster and segment organ images with fewer errors. However, existing methods are not efficient enough to perform the segmentation process for victims of accidents and emergencies situations. In this paper we propose...

Three dimensional (3D) contents such as 3D point clouds, 3D meshes and 3D surface models are increasingly growing and being widely spread into the industry and our daily life. However, less people consider the problem of the privacy preserving of 3D contents. As an attempt towards 3D security, in this papers, we propose methods of encrypting the 3D point clouds through chaotic mapping. 2 scheme...

Three-Dimensional Networks-on-Chip (3D-NoC) has been presented as an auspicious solution merging the high parallelism of Network-on-Chip (NoC) interconnect paradigm with the high-performance and lower interconnect-power of 3-dimensional integration circuits. However, 3D-NoC systems are exposed to a variety of manufacturing and design factors making them vulnerable to different faults that cause...

This study considers the 3D human pose estimation problem in a single RGB image by proposing a conditional random field (CRF) model over 2D poses, in which the 3D pose is obtained as a byproduct of the inference process. The unary term of the proposed CRF model is defined based on a powerful heat-map regression network, which has been proposed for 2D human pose estimation. This study also prese...

The use of 3D data in mobile robotics provides valuable information about the robot’s environment. Traditionally, stereo cameras have been used as a low-cost 3D sensor. However, the lack of precision and texture for some surfaces suggests that the use of other 3D sensors could be more suitable. In this work, we examine the use of two sensors: an infrared SR4000 and a Kinect camera. We use a com...

In this paper, we propose a novel video sequences compression and encryption method combining 3D compressive sensing (3D-CS) with 3D discrete fractional random transform (3D-DFrRT). In this scheme, the original video sequences were transformed with discrete wavelet and measured by three Gaussion random matrices to achieve compression and encryption simultaneously, and then the resulting 3D imag...

Three-dimensional (3D) integration and multi-level cell (MLC) are two attractive technologies to achieve ultra-high density for mass storage applications. In this work, a three-layer 3D vertical AlOδ/Ta2O5-x/TaOy resistive random access memories were fabricated and characterized. The vertical cells in three layers show good uniformity and high performance (e.g. >1000X HRS/LRS windows, >10(10) e...

Automatic liver segmentation from CT volumes is a crucial prerequisite yet challenging task for computer-aided hepatic disease diagnosis and treatment. In this paper, we present a novel 3D deeply supervised network (3D DSN) to address this challenging task. The proposed 3D DSN takes advantage of a fully convolutional architecture which performs efficient end-to-end learning and inference. More ...

The training algorithm of Wavelet Neural Networks (WNN) is a bottleneck which impacts on the accuracy of the final WNN model. Several methods have been proposed for training the WNNs. From the perspective of our research, most of these algorithms are iterative and need to adjust all the parameters of WNN. This paper proposes a one-step learning method which changes the weights between hidden la...