35 citations · 80 across the 13 of their papers we have counts for
13 papers
Thermal Cycling Reliability of Hybrid Pixel Sensor Modules for The ATLAS High Granularity Timing Detector
Y. Li, A. Aboulhorma, M. Ait Tamlihat +219
The reliability of bump connection structures has become a critical aspect of future silicon detectors for particle physics. The High Granularity Timing Detector (HGTD) for the ATL…
Signatures of a high-temperature collective electronic phase with superconductivity-like characteristics and a giant pressure effect in networks of boron-doped ultrathin carbon nanotubes
Y. Wang, T. H. Koo, R. Huang +11
We present data consistent with a high-temperature collective electronic phase with superconductivity-like characteristics in three dimensional networks of boron doped, ultrathin c…
Feature Calibration Network for Occluded Pedestrian Detection
Tianliang Zhang, Qixiang Ye, Baochang Zhang +3
Pedestrian detection in the wild remains a challenging problem especially for scenes containing serious occlusion. In this paper, we propose a novel feature learning method in the…
CircleNet: Reciprocating Feature Adaptation for Robust Pedestrian Detection
Tianliang Zhang, Zhenjun Han, Huijuan Xu +2
Pedestrian detection in the wild remains a challenging problem especially when the scene contains significant occlusion and/or low resolution of the pedestrians to be detected. Exi…
Predefined-time Stabilization for Nonlinear Stochastic Systems
Tianliang Zhang, Shengyuan Xu
In this paper, a control scheme for stochastic predefined-time stabilization is proposed, which improves the control effect compared with stochastic finite-time or fixed-time stabi…
LVIS Challenge Track Technical Report 1st Place Solution: Distribution Balanced and Boundary Refinement for Large Vocabulary Instance Segmentation
WeiFu Fu, CongChong Nie, Ting Sun +3
This report introduces the technical details of the team FuXi-Fresher for LVIS Challenge 2021. Our method focuses on the problem in following two aspects: the long-tail distributio…
Measurements of the growth and saturation of electron Weibel instability in optical-field ionized plasmas
Chaojie Zhang, Jianfei Hua, Yipeng Wu +11
The temporal evolution of the magnetic field associated with electron thermal Weibel instability in optical-field ionized plasmas is measured using ultrashort (1.8 ps), relativisti…
Multiple Anchor Learning for Visual Object Detection
Wei Ke, Tianliang Zhang, Zeyi Huang +3
Classification and localization are two pillars of visual object detectors. However, in CNN-based detectors, these two modules are usually optimized under a fixed set of candidate…
Mixed Fault Detection Filtering for Itô-Type Affine Nonlinear Stochastic Systems
Tianliang Zhang, Feiqi Deng, Weihai Zhang +1
This paper studies the mixed fault detection filtering of Itô-type nonlinear stochastic systems. Mixed filtering combines the system robustness to…
Robust Filtering for Nonlinear Discrete-time Stochastic Systems
Tianliang Zhang, Feiqi Deng, Weihai Zhang
This paper mainly discusses the filtering of general nonlinear discrete time-varying stochastic systems. A nonlinear discrete-time stochastic bounded real lemma (SBRL)…
Finite-time stability and stabilization of linear discrete time-varying stochastic systems
Tianliang Zhang, Feiqi Deng, Weihai Zhang
This paper studies the finite-time stability and stabilization of linear discrete time-varying stochastic systems with multiplicative noise. Firstly, necessary and sufficient condi…
New Approach to General Nonlinear Discrete-Time Stochastic Control
Xiangyun Lin, Tianliang Zhang, Weihai Zhang +1
In this paper, a new approach based on convex analysis is introduced to solve the problem for discrete-time nonlinear stochastic systems. A stochastic version of bounded…
Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model
Qixiang Ye, Tianliang Zhang, Qiang Qiu +3
In this paper, a self-learning approach is proposed towards solving scene-specific pedestrian detection problem without any human' annotation involved. The self-learning approach i…