Search Results for author: Cheng Peng

Found 30 papers, 6 papers with code

Enhanced Sentence Alignment Network for Efficient Short Text Matching

no code implementations EMNLP (WNUT) 2020 Zhe Hu, Zuohui Fu, Cheng Peng, Weiwei Wang

Cross-sentence attention has been widely applied in text matching, in which model learns the aligned information between two intermediate sequence representations to capture their semantic relationship.

Text Matching

Undersampled MRI Reconstruction with Side Information-Guided Normalisation

no code implementations7 Mar 2022 Xinwen Liu, Jing Wang, Cheng Peng, Shekhar S. Chandra, Feng Liu, S. Kevin Zhou

In this paper, we investigate the use of such side information as normalisation parameters in a convolutional neural network (CNN) to improve undersampled MRI reconstruction.

MRI Reconstruction

HyperSegNAS: Bridging One-Shot Neural Architecture Search with 3D Medical Image Segmentation using HyperNet

no code implementations20 Dec 2021 Cheng Peng, Andriy Myronenko, Ali Hatamizadeh, Vish Nath, Md Mahfuzur Rahman Siddiquee, Yufan He, Daguang Xu, Rama Chellappa, Dong Yang

Given the recent success of deep learning in medical image segmentation, Neural Architecture Search (NAS) has been introduced to find high-performance 3D segmentation network architectures.

Medical Image Segmentation Neural Architecture Search +1

RSBNet: One-Shot Neural Architecture Search for A Backbone Network in Remote Sensing Image Recognition

no code implementations7 Dec 2021 Cheng Peng, Yangyang Li, Ronghua Shang, Licheng Jiao

Recently, a massive number of deep learning based approaches have been successfully applied to various remote sensing image (RSI) recognition tasks.

Neural Architecture Search Object Detection +1

GAN-based disentanglement learning for chest X-ray rib suppression

no code implementations18 Oct 2021 Luyi Han, Yuanyuan Lyu, Cheng Peng, S. Kevin Zhou

Clinical evidence has shown that rib-suppressed chest X-rays (CXRs) can improve the reliability of pulmonary disease diagnosis.

Computed Tomography (CT) Disentanglement +1

U-DuDoNet: Unpaired dual-domain network for CT metal artifact reduction

no code implementations8 Mar 2021 Yuanyuan Lyu, Jiajun Fu, Cheng Peng, S. Kevin Zhou

Recently, both supervised and unsupervised deep learning methods have been widely applied on the CT metal artifact reduction (MAR) task.

Disentanglement Metal Artifact Reduction

Portfolio Optimization on Multivariate Regime Switching GARCH Model with Normal Tempered Stable Innovation

no code implementations23 Sep 2020 Cheng Peng, Young Shin Kim

We propose a Markov regime switching GARCH model with multivariate normal tempered stable innovation to accommodate fat tails and other stylized facts in returns of financial assets.

Portfolio Optimization

SAINT: Spatially Aware Interpolation NeTwork for Medical Slice Synthesis

no code implementations CVPR 2020 Cheng Peng, Wei-An Lin, Haofu Liao, Rama Chellappa, S. Kevin Zhou

Deep learning-based single image super-resolution (SISR) methods face various challenges when applied to 3D medical volumetric data (i. e., CT and MR images) due to the high memory cost and anisotropic resolution, which adversely affect their performance.

Image Super-Resolution

Ellipse R-CNN: Learning to Infer Elliptical Object from Clustering and Occlusion

no code implementations30 Jan 2020 Wenbo Dong, Pravakar Roy, Cheng Peng, Volkan Isler

We first propose a robust and compact ellipse regression based on the Mask R-CNN architecture for elliptical object detection.

Object Detection Occlusion Handling

Entanglement and Confinement in Coupled Quantum Systems

no code implementations9 Jan 2020 Fabien Alet, Masanori Hanada, Antal Jevicki, Cheng Peng

We also consider the coupled gauged matrix model and vector model, and argue that the deconfinement is associated with the loss of the entanglement, similarly to the previous observation for the coupled SYK model.

High Energy Physics - Theory Strongly Correlated Electrons

Idle Time Optimization for Target Assignment and Path Finding in Sortation Centers

no code implementations30 Nov 2019 Ngai Meng Kou, Cheng Peng, Hang Ma, T. K. Satish Kumar, Sven Koenig

In this paper, we study the one-shot and lifelong versions of the Target Assignment and Path Finding problem in automated sortation centers, where each agent needs to constantly assign itself a sorting station, move to its assigned station without colliding with obstacles or other agents, wait in the queue of that station to obtain a parcel for delivery, and then deliver the parcel to a sorting bin.

Unsupervised Many-to-Many Image-to-Image Translation Across Multiple Domains

no code implementations28 Nov 2019 Ye Lin, Keren Fu, Shenggui Ling, Cheng Peng

To improve the image quality, we propose an effective many-to-many mapping framework for unsupervised multi-domain image-to-image translation.

Translation Unsupervised Image-To-Image Translation

Potential Field: Interpretable and Unified Representation for Trajectory Prediction

no code implementations18 Nov 2019 Shan Su, Cheng Peng, Jianbo Shi, Chiho Choi

From the generated potential fields, we further estimate future motion direction and speed, which are modeled as Gaussian distributions to account for the multi-modal nature of the problem.

Trajectory Prediction

DG-GAN: the GAN with the duality gap

no code implementations25 Sep 2019 Cheng Peng, Hao Wang, Xiao Wang, Zhouwang Yang

Generative Adversarial Networks (GANs) are powerful, but difficult to understand and train because GANs is a min-max problem.

Map as The Hidden Sensor: Fast Odometry-Based Global Localization

no code implementations20 Sep 2019 Cheng Peng, David Weikersdorfer

The resulting map-corrected odometry localization is able to provide an accurate belief tensor of the robot state.

Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement

no code implementations15 Aug 2019 Cheng Peng, Wei-An Lin, Haofu Liao, Rama Chellappa, S. Kevin Zhou

We propose a marginal super-resolution (MSR) approach based on 2D convolutional neural networks (CNNs) for interpolating an anisotropic brain magnetic resonance scan along the highly under-sampled direction, which is assumed to axial without loss of generality.

Semantic Segmentation Super-Resolution

DuDoNet: Dual Domain Network for CT Metal Artifact Reduction

no code implementations CVPR 2019 Wei-An Lin, Haofu Liao, Cheng Peng, Xiaohang Sun, Jingdan Zhang, Jiebo Luo, Rama Chellappa, Shaohua Kevin Zhou

The linkage between the sigogram and image domains is a novel Radon inversion layer that allows the gradients to back-propagate from the image domain to the sinogram domain during training.

Computed Tomography (CT) Medical Diagnosis +1

Generative Tensor Network Classification Model for Supervised Machine Learning

no code implementations26 Mar 2019 Zheng-Zhi Sun, Cheng Peng, Ding Liu, Shi-Ju Ran, Gang Su

By investigating the distances in the many-body Hilbert space, we find that (a) the samples are naturally clustering in such a space; and (b) bounding the bond dimensions of the TN's to finite values corresponds to removing redundant information in the image recognition.

Classification General Classification

Quantum simulation for thermodynamics of infinite-size many-body systems by O(10) sites

1 code implementation3 Oct 2018 Shi-Ju Ran, Bin Xi, Cheng Peng, Gang Su, Maciej Lewenstein

In this work we propose to simulate many-body thermodynamics of infinite-size quantum lattice models in one, two, and three dimensions, in terms of few-body models of only O(10) sites, which we coin as quantum entanglement simulators (QES's).

Strongly Correlated Electrons Computational Physics Quantum Physics

Adaptive View Planning for Aerial 3D Reconstruction

no code implementations1 May 2018 Cheng Peng, Volkan Isler

We then present (i)~a method that builds a view manifold for view selection, and (ii) an algorithm to select a sparse set of views.

3D Reconstruction

Review of Tensor Network Contraction Approaches

1 code implementation30 Aug 2017 Shi-Ju Ran, Emanuele Tirrito, Cheng Peng, Xi Chen, Gang Su, Maciej Lewenstein

One goal is to provide a systematic introduction of TN contraction algorithms (motivations, implementations, relations, implications, etc.

Computational Physics Statistical Mechanics Strongly Correlated Electrons Applied Physics Quantum Physics

A Fast Integrated Planning and Control Framework for Autonomous Driving via Imitation Learning

no code implementations9 Jul 2017 Liting Sun, Cheng Peng, Wei Zhan, Masayoshi Tomizuka

For safe and efficient planning and control in autonomous driving, we need a driving policy which can achieve desirable driving quality in long-term horizon with guaranteed safety and feasibility.

Autonomous Driving Imitation Learning

View Selection with Geometric Uncertainty Modeling

no code implementations31 Mar 2017 Cheng Peng, Volkan Isler

Consider a world point $g \in \mathcal{G}$ and its worst case reconstruction uncertainty $\varepsilon(g,\mathcal{S})$ obtained by merging \emph{all} possible views of $g$ chosen from $\mathcal{S}$.

3D Reconstruction Simultaneous Localization and Mapping

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