We report ab initio band diagram and optical absorption spectra of hexagonal boron nitride (h-BN), focusing on unravelling how the completeness of basis set for GW calculations and how electron-phonon interactions (EP...
详细信息
Drawing support from an effective Medical Image Segmentation (MIS) is conducive to a substantial diagnostic basis for the physicians to identify the focus lesion in the patient body and give the subsequent clinical as...
详细信息
ISBN:
(纸本)9781665429825
Drawing support from an effective Medical Image Segmentation (MIS) is conducive to a substantial diagnostic basis for the physicians to identify the focus lesion in the patient body and give the subsequent clinical assessment of the patient status. Although various works have tried the challenging quantitative analysis problem, it is still difficult to conduct precise automatic segmentation, especially the soft tissue organs. In this decade, with the increased amount of available datasets, deep learning-based networks have achieved remarkable performance in image processing. Inspired by the state-of-the-art deep learning works, in this paper, we propose an end-to-end multi-layer network named RCGA-Net. It consists of an encoder-decoder backbone that integrates a coordinate attention mechanism based on space and channel and a global context extraction module to highlight more valuable information. To evaluate the performance of RCGA-Net, we apply it to different kinds of clinical and experimental MIS tasks to testify its generalization ability. Extensive experiments represent that our schema has taken the outperform or compatible results among the comparison methods group. Specifically, the numeric result of RCGA-Net on the pulmonary dataset has achieved a 99.12% optimum F1-score.
Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI)widely used for visualizing diseased cardiacstructures, is a crucial first step for clinical diagnosis and trea...
详细信息
三维集成电路是通过硅通孔将多个相同或不同工艺的晶片上下堆叠并进行垂直集成的新兴芯片集成技术。通过这种集成,芯片可获得更小的外形尺寸、更高的片上晶体管集成密度、单片上能集成更多的功能模块以及更高的互连性能等显著优点。然而,三维集成电路也带来了诸如TSV电迁移效应等新挑战。本文提出了一种抑制TSV电迁移效应的可靠性设计方法。首先,针对镀铜气泡、绑定非对齐和绑定界面尘埃沾染等TSV缺陷,分析了制造缺陷和电迁移效应之间的关系。通过观察发现,制造缺陷在加剧电迁移效应的同时还会影响TSV的阻值。然后,本文提出了TSV-SAFE(TSV Self-healing architecture For Electro-migration)可靠性设计框架抑制电迁移效应。实验中,本文构建了一个由两层电路组成的3D芯片仿真平台。实验结果表明,采用本文所提出的技术,TSV的平均无故障时间(MTTF)平均增加了70倍,而由此带来的硬件面积开销不超过全芯片面积的1％。
暂无评论