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Harpreet Sawhney

Also published under: H. S. Sawhney, Harpreet S. Sawhney, H. Sawhney

Publications

Citations

5,382

Publications by Year

19902023

Co-Authors:

M. AggarwalSaad AliMohamed R. AmerP. AnandanJ. Ashley

Show All Co-Authors (104)

Harpreet Sawhney

Also published under: H. S. Sawhney, Harpreet S. Sawhney, H. Sawhney

Affiliation

Microsoft Mixed Reality

Publication Topics

Object Detection,
Optical Flow,
Binary Classification,
Corresponding Points,
Deep Learning,
Feature Representation,
Fine-tuned,
Image Point,
Pretext Task,
Raw Features,
Self-supervised Learning,
Temporal Model

Biography

Harpreet Sawhney (Member IEEE) received the Ph.D. degree in computer science from the University of Massachusetts, Amherst, in 1992, focusing on Computer Vision.,He is a Senior Member, Technical Staff in the Vision Technologies Laboratory at Sarnoff Corporation, Princeton, NJ, where he has led R&D in 3-D modeling and manipulation from motion video, video enhancement and indexing, and video mosaicing, under a number of commercial and government programs since 1995. He led R&D in video annotation and indexing at the IBM Almaden Research Center from 1992 to 1995. He has authored over 40 technical publications, holds five patents, and has a number of patent applications pending.(Based on document published on 7 August 2002).

Publications

Citations

5,382

Publications by Year

19902023

Co-Authors:

M. Aggarwal
Saad Ali
Mohamed R. Amer
P. Anandan
J. Ashley

Show All Co-Authors (104)

Author's Published Works

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Conferences (2)

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Lin Chen(2)
Xue Jiang(2)
Zhimeng Zhong(1)
Zhentao Zou(1)
Pei Xiao(1)
Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China(1)
Communications Research Laboratory, Ilmenau University of Technology, Ilmenau, Germany(1)
School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China(1)
Wireless Network RAN Research Department, Huawei Technologies Co. LTD, Shanghai, China(1)
Institute for Communication Systems, University of Surrey, Guildford, U.K(1)
2021 55th Asilomar Conference on Signals, Systems, and Computers(1)
2023 31st European Signal Processing Conference (EUSIPCO)(1)
IEEE(2)
Helsinki, Finland(1)
Pacific Grove, CA, USA(1)
Channel Estimation(2)
Downlink Channel(2)
Frequency Division Duplex(2)
Massive Multiple-input Multiple-output(2)
Massive Multiple-input Multiple-output Systems(2)

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Downlink Channel Estimation in FDD Massive MIMO Systems Based on Multi-Resolution Discrimination Dictionary Learning

Zhentao Zou;Lin Chen;Xue Jiang;Pei Xiao

2023 31st European Signal Processing Conference (EUSIPCO)

Year: 2023 | Conference Paper |

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Compressive sensing (CS) techniques can be used to reduce the pilot overhead, and to improve the performance of channel estimation in massive multiple-input multiple-output (MIMO) systems. Most existing methods adopt the DFT matrix as a basis, which leads to direction mismatch and energy leakage problem in practice. However, the properties of geometry-based stochastic channel model (GSCM) are usua...Show More

Downlink Channel Estimation in FDD Massive MIMO Systems Based on Multi-Resolution Discrimination Dictionary Learning

Zhentao Zou;Lin Chen;Xue Jiang;Pei Xiao

2023 31st European Signal Processing Conference (EUSIPCO)

Year: 2023 | Conference Paper |

Tensor-Based Downlink Channel Reconstruction for FDD Massive MIMO

Lin Chen;Xue Jiang;Zhimeng Zhong;Xingzhao Liu;Martin Haardt

2021 55th Asilomar Conference on Signals, Systems, and Computers

Year: 2021 | Conference Paper |

Cited by: Papers (5)

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The acquisition of downlink channel state information (CSI) at the base station is a prerequisite for various applications in frequency division duplex (FDD) massive multipleinput multiple-output (MIMO) systems. To obtain accurate CSI, conventional approaches employ downlink training and feedback with a considerable overhead. In this paper, we exploit the partial reciprocity between FDD uplink and...Show More

Tensor-Based Downlink Channel Reconstruction for FDD Massive MIMO

Lin Chen;Xue Jiang;Zhimeng Zhong;Xingzhao Liu;Martin Haardt

2021 55th Asilomar Conference on Signals, Systems, and Computers

Year: 2021 | Conference Paper |

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