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Research.com Recognitions

  • 2018 - IEEE Fellow For contributions to cooperative diversity and development of distributed turbo codes

Overview

Matthew C. Valenti is affiliated with West Virginia University in the United States. Their research primarily spans the fields of Computer Science and Engineering, with particular focus on subfields including Computer Vision and Pattern Recognition, Aerospace Engineering, Electrical and Electronic Engineering, Signal Processing, and Computer Networks and Communications.

Their work encompasses a range of main topics such as Face Recognition and Analysis, Biometric Identification and Security, Face and Expression Recognition, UAV Applications and Optimization, Generative Adversarial Networks and Image Synthesis, Advanced Image and Video Retrieval Techniques, and Wireless Communication Networks Research.

Among their recent publications are:

  • Attribute-Based Deep Periocular Recognition: Leveraging Soft Biometrics to Improve Periocular Recognition (2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV))
  • Error-Corrected Margin-Based Deep Cross-Modal Hashing for Facial Image Retrieval (2020, IEEE Transactions on Biometrics Behavior and Identity Science)
  • Profile to frontal face recognition in the wild using coupled conditional generative adversarial network (2022, IET Biometrics)
  • Empirical Assessment of End-to-End Iris Recognition System Capacity (2023, IEEE Transactions on Biometrics Behavior and Identity Science)
  • Profile to Frontal Face Recognition in the Wild Using Coupled Conditional GAN (2021, arXiv (Cornell University))

They frequently publish in venues such as arXiv (Cornell University), IEEE Transactions on Biometrics Behavior and Identity Science, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), IET Biometrics, and MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM).

Frequent collaborators include Veeru Talreja, Nasser M. Nasrabadi, Fariborz Taherkhani, Natalia A. Schmid, and Joseph D. Skufca.

In 2018, Matthew C. Valenti received recognition as an IEEE Fellow for contributions to cooperative diversity and the development of distributed turbo codes.

Best Publications

  • Practical relay networks: a generalization of hybrid-ARQ

    Bin Zhao;M.C. Valenti

  • Distributed turbo coded diversity for relay channel

    B. Zhao;M.C. Valenti

  • Iterative channel estimation and decoding of pilot symbol assisted turbo codes over flat-fading channels

    M.C. Valenti;B.D. Woerner

  • Asynchronous cooperative diversity

    Shuangqing Wei;D.L. Goeckel;M.C. Valenti

  • The UMTS Turbo Code and an Efficient Decoder Implementation Suitable for Software-Defined Radios

    Matthew C. Valenti;Jian Sun

  • Device-to-Device Millimeter Wave Communications: Interference, Coverage, Rate, and Finite Topologies

    Kiran Venugopal;Matthew C. Valenti;Robert W. Heath

  • Distributed turbo codes: towards the capacity of the relay channel

    M.C. Valenti;Bin Zhao

  • Iterative demodulation and decoding of turbo-coded M-ary noncoherent orthogonal modulation

    M.C. Valenti;Shi Cheng

  • Iterative Detection and Decoding for Wireless Communications

    Matthew C. Valenti

  • On the throughput of Bluetooth data transmissions

    M.C. Valenti;M. Robert;J.H. Reed

  • The Outage Probability of a Finite Ad Hoc Network in Nakagami Fading

    D. Torrieri;M. C. Valenti

  • Interference in finite-sized highly dense millimeter wave networks

    Kiran Venugopal;Matthew C. Valenti;Robert W. Heath

  • Coded transmit macrodiversity: block space-time codes over distributed antennas

    Yipeng Tang;M.C. Valenti

  • Performance of turbo codes in interleaved flat fading channels with estimated channel state information

    M.C. Valenti;B.D. Woerner

  • Benefits and challenges of virtualization in 5G radio access networks

    Peter Rost;Ignacio Berberana;Andreas Maeder;Henning Paul

  • Multibiometric secure system based on deep learning

    Veeru Talreja;Matthew C. Valenti;Nasser M. Nasrabadi

  • Constellation Shaping for Bit-Interleaved LDPC Coded APSK

    Matthew C. Valenti;Xingyu Xiang

  • Refined channel estimation for coherent detection of turbo codes over flat-fading channels

    M.C. Valenti;B.D. Woerner

  • Exploiting macrodiversity in dense multihop networks and relay channels

    M.C. Valenti;N. Correal

  • The Complexity–Rate Tradeoff of Centralized Radio Access Networks

    Peter Rost;Salvatore Talarico;Matthew C. Valenti

Frequent Co-Authors

Nasser M. Nasrabadi
Nasser M. Nasrabadi West Virginia University
Robert W. Heath
Robert W. Heath University of California, San Diego
Arun Ross
Arun Ross Michigan State University
Ender Ayanoglu
Ender Ayanoglu University of California, Irvine
Jeffrey H. Reed
Jeffrey H. Reed Virginia Tech
Dennis Goeckel
Dennis Goeckel University of Massachusetts Amherst
Abbas Jamalipour
Abbas Jamalipour University of Sydney
Marco Di Renzo
Marco Di Renzo CentraleSupélec
xin li
xin li Louisiana State University

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