120 research outputs found
Feature-aware uniform tessellations on video manifold for content-sensitive supervoxels
Over-segmenting a video into supervoxels has strong potential to reduce the complexity of computer vision applications. Content-sensitive supervoxels (CSS) are typically smaller in content-dense regionsand larger in content-sparse regions. In this paper, we propose to compute feature-aware CSS (FCSS) that are regularly shaped 3D primitive volumes well aligned with local object/region/motion boundaries in video.To compute FCSS, we map a video to a 3-dimensional manifold, in which the volume elements of video manifold give a good measure of the video content density. Then any uniform tessellation on manifold can induce CSS. Our idea is that among all possible uniform tessellations, FCSS find one whose cell boundaries well align with local video boundaries. To achieve this goal, we propose a novel tessellation method that simultaneously minimizes the tessellation energy and maximizes the average boundary distance.Theoretically our method has an optimal competitive ratio O(1). We also present a simple extension of FCSS to streaming FCSS for processing long videos that cannot be loaded into main memory at once. We evaluate FCSS, streaming FCSS and ten representative supervoxel methods on four video datasets and two novel video applications. The results show that our method simultaneously achieves state-of-the-art performance with respect to various evaluation criteria
AI-Oriented Two-Phase Multi-Factor Authentication in SAGINs: Prospects and Challenges
Space-air-ground integrated networks (SAGINs), which have emerged as an
expansion of terrestrial networks, provide flexible access, ubiquitous
coverage, high-capacity backhaul, and emergency/disaster recovery for mobile
users (MUs). While the massive benefits brought by SAGIN may improve the
quality of service, unauthorized access to SAGIN entities is potentially
dangerous. At present, conventional crypto-based authentication is facing
challenges, such as the inability to provide continuous and transparent
protection for MUs. In this article, we propose an AI-oriented two-phase
multi-factor authentication scheme (ATMAS) by introducing intelligence to
authentication. The satellite and network control center collaborate on
continuous authentication, while unique spatial-temporal features, including
service features and geographic features, are utilized to enhance the system
security. Our further security analysis and performance evaluations show that
ATMAS has proper security characteristics which can meet various security
requirements. Moreover, we shed light on lightweight and efficient
authentication mechanism design through a proper combination of
spatial-temporal factors.Comment: Accepted by IEEE Consumer Electronics Magazin
GAN-based multi-style photo cartoonization
Cartoon is a common form of art in our daily life and automatic generation of cartoon images from photos is highly desirable. However, state-of-the-art single-style methods can only generate one style of cartoon images from photos and existing multi-style image style transfer methods still struggle to produce high-quality cartoon images due to their highly simplified and abstract nature. In this paper, we propose a novel multi-style generative adversarial network (GAN) architecture, called MS-CartoonGAN, which can transform photos into multiple cartoon styles. We develop a multi-domain architecture, where the generator consists of a shared encoder and multiple decoders for different cartoon styles, along with multiple discriminators for individual styles. By observing that cartoon images drawn by different artists have their unique styles while sharing some common characteristics, our shared network architecture exploits the common characteristics of cartoon styles, achieving better cartoonization and being more efficient than single-style cartoonization. We show that our multi-domain architecture can theoretically guarantee to output desired multiple cartoon styles. Through extensive experiments including a user study, we demonstrate the superiority of the proposed method, outperforming state-of-the-art single-style and multi-style image style transfer methods
Wafer-scale growth of large arrays of perovskite microplate crystals for functional electronics and optoelectronics
Methylammonium lead iodide perovskite has attracted intensive interest for
its diverse optoelectronic applications. However, most studies to date have
been limited to bulk thin films that are difficult to implement for integrated
device arrays because of their incompatibility with typical lithography
processes. We report the first patterned growth of regular arrays of perovskite
microplate crystals for functional electronics and optoelectronics. We show
that large arrays of lead iodide microplates can be grown from an aqueous
solution through a seeded growth process and can be further intercalated with
methylammonium iodide to produce perovskite crystals. Structural and optical
characterizations demonstrate that the resulting materials display excellent
crystalline quality and optical properties. We further show that perovskite
crystals can be selectively grown on prepatterned electrode arrays to create
independently addressable photodetector arrays and functional field effect
transistors. The ability to grow perovskite microplates and to precisely place
them at specific locations offers a new material platform for the fundamental
investigation of the electronic and optical properties of perovskite materials
and opens a pathway for integrated electronic and optoelectronic systems.Comment: 8 pages, 4 figure
T cell-related ubiquitination genes as prognostic indicators in hepatocellular carcinoma
BackgroundT lymphocytes, integral to the adaptive immune system, wield pivotal influence in bolstering anti-tumor responses, and are strictly regulated by ubiquitination modification. The objective of this investigation was to devise a novel prognostic and immunotherapeutic efficacy predictor for hepatocellular carcinoma patients utilizing T cell-related ubiquitination genes (TCRUG).MethodThe single-cell RNA sequencing (scRNA-seq) data and bulk RNA data of HCC patients are derived from the GEO database and TCGA database. Based on the processing of scRNA-seq, T cell marker genes are obtained and TCRUG is obtained. Further combined with WGCNA, differential analysis, univariate Cox regression analysis, LASSO analysis, and multivariate Cox regression analysis to filter and screen TCRUG. Finally construct a riskscore for predicting the prognosis of HCC patients, the predictive effect of which is validated in the GEO dataset. In addition, we also studied the correlation between riskscore and immunotherapy efficacy. Finally, the oncogenic role of UBE2E1 in HCC was explored through various in vitro experiments.ResultBased on patients’ scRNA-seq data, we finally obtained 3050 T cell marker genes. Combined with bulk RNA data and clinical data from the TCGA database, we constructed a riskscore that accurately predicts the prognosis of HCC patients. This riskscore is an independent prognostic factor for HCC and is used to construct a convenient column chart. In addition, we found that the high-risk group is more suitable for immunotherapy. Finally, the proliferation, migration, and invasion abilities of HCC cells significantly decreased after UBE2E1 expression reduction.ConclusionThis study developed a riskscore based on TCRUG that can accurately and stably predict the prognosis of HCC patients. This riskscore is also effective in predicting the immune therapy response of HCC patients
Ultrafine jagged platinum nanowires enable ultrahigh mass activity for the oxygen reduction reaction
Amine-Assisted Synthesis of Concave Polyhedral Platinum Nanocrystals Having {411} High-Index Facets
通讯作者地址: Zheng, NF (通讯作者), Xiamen Univ, State Key Lab Phys Chem Solid Surfaces, Xiamen 361005, Peoples R China
地址:
1. Xiamen Univ, State Key Lab Phys Chem Solid Surfaces, Xiamen 361005, Peoples R China
2. Xiamen Univ, Dept Chem, Coll Chem & Chem Engn, Xiamen 361005, Peoples R China
电子邮件地址: [email protected] surfaces of a face-centered cubic metal (e.g., Pd, Pt) have a high density of low-coordinated surface atoms and therefore possess enhanced catalysis activity in comparison with low-index faces. However, because of their high surface energy, the challenge of chemically preparing metal nanocrystals having high-index facets remains. We demonstrate in this work that introducing amines as the surface controller allows concave Pt nanocrystals having {411} high-index facets to be prepared through a facile wet-chemical route. The as-prepared Pt nanocrystals display a unique octapod morphology with {411} facets. The presence of high-index {411} exposed facets endows the concave Pt nanocrystals with excellent electrocatalytic activity in the oxidation of both formic acid and ethanol.NSFC 21021061
20925103
20923004
20871100
Fok Ying Tung Education Foundation 121011
MOST of China 2011CB932403
2009CB930703
NFFTBS J1030415
NSF of Fujian Province 2009J06005
Key Scientific Project of Fujian Province 2009HZ0002-
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