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63 Awards found.



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  •  AWARD    Japan Telecommunications Advancement Foundation Award
    Date: March 15, 2022
    Awarded to: Yukimasa Nagai, Jianlin Guo, Philip Orlik, Takenori Sumi, Benjamin A. Rolfe and Hiroshi Mineno
    MERL Contacts: Jianlin Guo; Philip V. Orlik
    Research Areas: Communications, Machine Learning
    Brief
    • MELCO/MERL research paper “Sub-1 GHz Frequency Band Wireless Coexistence for the Internet of Things” has won the 37th Telecommunications Advancement Foundation Award (Telecom System Technology Award) in Japan. This award started in 1984, and is given to research papers and works related to information and telecommunications that have made significant contributions and achievements to the advancement, development, and standardization of information and telecommunications from technical and engineering perspectives. The award recognizes both the IEEE 802.19.3 standardization efforts and the technological advancements using reinforcement learning and robust access methodologies for wireless communication system. This year, there were 43 entries with 5 winning awards and 3 winning encouragement awards. This is the first time MELCO/MERL has received this award. Our paper has been published by IEEE Access in 2021 and authors are Yukimasa Nagai, Jianlin Guo, Philip Orlik, Takenori Sumi, Benjamin A. Rolfe and Hiroshi Mineno.
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  •  AWARD    Joshua Rapp wins Best Dissertation Award from the IEEE Signal Processing Society
    Date: December 20, 2021
    Awarded to: Joshua Rapp
    MERL Contact: Joshua Rapp
    Research Areas: Computational Sensing, Signal Processing
    Brief
    • Joshua Rapp has won the 2021 Best PhD Dissertation Award from the IEEE Signal Processing Society.
      The award recognizes a PhD thesis completed on a signal processing subject within the past three years for its relevant work in signal processing while stimulating further research in the field.

      Dr. Rapp completed his PhD at Boston University in 2020 with a thesis entitled "Probabilistic Modeling for Single-Photon Lidar." The dissertation tackles challenges of the acquisition and processing of 3D depth maps reconstructed from time-of-flight data captured one photon at a time.
      The award will be presented at the 2022 IEEE International Conference on Image Processing (ICIP) in France.
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  •  AWARD    Petros Boufounos Elevated to IEEE Fellow
    Date: January 1, 2022
    Awarded to: Petros T. Boufounos
    MERL Contact: Petros T. Boufounos
    Research Areas: Computational Sensing, Signal Processing
    Brief
    • MERL’s Petros Boufounos has been elevated to IEEE Fellow, effective January 2022, for “contributions to compressed sensing.”

      IEEE Fellow is the highest grade of membership of the IEEE. It honors members with an outstanding record of technical achievements, contributing importantly to the advancement or application of engineering, science and technology, and bringing significant value to society. Each year, following a rigorous evaluation procedure, the IEEE Fellow Committee recommends a select group of recipients for elevation to IEEE Fellow. Less than 0.1% of voting members are selected annually for this member grade elevation.
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  •  AWARD    Toshiaki Koike-Akino elected Fellow of Optica
    Date: November 18, 2021
    Awarded to: Toshiaki Koike-Akino
    MERL Contact: Toshiaki Koike-Akino
    Research Areas: Communications, Electronic and Photonic Devices, Signal Processing
    Brief
    • Toshiaki Koike-Akino's research activities in communications, error control coding and optical technologies at MERL have earned him election as a Fellow Member of Optica (formerly OSA), the foremost professional association in optics and photonics worldwide. Fellow membership in Optica is limited to no more than ten percent of the membership and is reserved for members who have served with distinction in the advancement of optics and photonics. Koike-Akino is one of 106 members from 24 countries in Optica’s 2022 Fellows Class, elected during the Board of Directors of Optica meeting held on 2nd of November, 2021.

      “Congratulations to the 2022 Optica Fellows,” said 2021 President Connie Chang-Hasnain, University of California, Berkeley, USA. “These members exemplify what it means to be a leader in optics and photonics. Your election, by your peers, confirms the important contributions made within our field. Thank you for your dedication to Optica, and for advancing the science of light.”

      Koike-Akino's elevation to Fellow is specifically “for outstanding and innovative contributions to R&D in enabling technologies for optical communications, including nonlinear equalizers, high-dimensional modulations, and FEC (Forward Error Correction),” said Meredith Smith, Director, Optica Awards and Honors Office. "Again, congratulations on joining this esteemed group of Optica members."

      About Optica

      Optica (formerly OSA) is dedicated to promoting the generation, application, archiving and dissemination of knowledge in optics and photonics worldwide. Founded in 1916, it is the leading organization for scientists, engineers, business professionals, students and others interested in the science of light. Optica’s renowned publications, meetings, online resources and in-person activities fuel discoveries, shape real-life applications and accelerate scientific, technical and educational achievement.
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  •  AWARD    Mitsubishi Electric US Receives a 2022 CES Innovation Award for Touchless Elevator Control Jointly Developed with MERL
    Date: November 17, 2021
    Awarded to: Elevators and Escalators Division of Mitsubishi Electric US, Inc.
    MERL Contacts: Daniel N. Nikovski; William S. Yerazunis
    Research Areas: Data Analytics, Machine Learning, Signal Processing
    Brief
    • The Elevators and Escalators Division of Mitsubishi Electric US, Inc. has been recognized as a 2022 CES® Innovation Awards honoree for its new PureRide™ Touchless Control for elevators, jointly developed with MERL. Sponsored by the Consumer Technology Association (CTA), the CES Innovation Awards is the largest and most influential technology event in the world. PureRide™ Touchless Control provides a simple, no-touch product that enables users to call an elevator and designate a destination floor by placing a hand or finger over a sensor. MERL initiated the development of PureRide™ in the first weeks of the COVID-19 pandemic by proposing the use of infra-red sensors for operating elevator call buttons, and participated actively in its rapid implementation and commercialization, resulting in a first customer installation in October of 2020.
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  •  AWARD    MERL Ranked 1st Place in Cross-Subject Transfer Learning Task and 4th Place Overall at the NeurIPS2021 BEETL Competition for EEG Transfer Learning.
    Date: November 11, 2021
    Awarded to: Niklas Smedemark-Margulies, Toshiaki Koike-Akino, Ye Wang, Deniz Erdogmus
    MERL Contacts: Toshiaki Koike-Akino; Ye Wang
    Research Areas: Artificial Intelligence, Signal Processing, Human-Computer Interaction
    Brief
    • The MERL Signal Processing group achieved first place in the cross-subject transfer learning task and fourth place overall in the NeurIPS 2021 BEETL AI Challenge for EEG Transfer Learning. The team included Niklas Smedemark-Margulies (intern from Northeastern University), Toshiaki Koike-Akino, Ye Wang, and Prof. Deniz Erdogmus (Northeastern University). The challenge addresses two types of transfer learning tasks for EEG Biosignals: a homogeneous transfer learning task for cross-subject domain adaptation; and a heterogeneous transfer learning task for cross-data domain adaptation. There were 110+ registered teams in this competition, MERL ranked 1st in the homogeneous transfer learning task, 7th place in the heterogeneous transfer learning task, and 4th place for the combined overall score. For the homogeneous transfer learning task, MERL developed a new pre-shot learning framework based on feature disentanglement techniques for robustness against inter-subject variation to enable calibration-free brain-computer interfaces (BCI). MERL is invited to present our pre-shot learning technique at the NeurIPS 2021 workshop.
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  •  AWARD    Daniel Nikovski receives Outstanding Reviewer Award at NeurIPS'21
    Date: October 18, 2021
    Awarded to: Daniel Nikovski
    MERL Contact: Daniel N. Nikovski
    Research Areas: Artificial Intelligence, Machine Learning
    Brief
    • Daniel Nikovski, Group Manager of MERL's Data Analytics group, has received an Outstanding Reviewer Award from the 2021 conference on Neural Information Processing Systems (NeurIPS'21). NeurIPS is the world's premier conference on neural networks and related technologies.
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  •  AWARD    Excellent Presentation Award
    Date: January 25, 2021
    Awarded to: Takenori Sumi, Yukimasa Nagai, Jianlin Guo, Philip Orlik, Tatsuya Yokoyama, Hiroshi Mineno
    MERL Contacts: Jianlin Guo; Philip V. Orlik
    Research Areas: Communications, Machine Learning, Signal Processing
    Brief
    • MELCO and MERL researchers have won "Excellent Presentation Award" at the IPSJ/CDS30 (Information Processing Society of Japan/Consumer Devices and Systems 30th conferences) held on January 25, 2021. The paper titled "Sub-1 GHz Coexistence Using Reinforcement Learning Based IEEE 802.11ah RAW Scheduling" addresses coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. This paper proposes a novel method to allocate IEEE 802.11 RAW time slots using a Q-Learning technique. MERL and MELCO have been leading IEEE 802.19.3 coexistence standard development and this paper is a good candidate for future standard enhancement. The authors are Takenori Sumi, Yukimasa Nagai, Jianlin Guo, Philip Orlik, Tatsuya Yokoyama and Hiroshi Mineno.
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  •  AWARD    Best Paper - Honorable Mention Award at WACV 2021
    Date: January 6, 2021
    Awarded to: Rushil Anirudh, Suhas Lohit, Pavan Turaga
    MERL Contact: Suhas Lohit
    Research Areas: Computational Sensing, Computer Vision, Machine Learning
    Brief
    • A team of researchers from Mitsubishi Electric Research Laboratories (MERL), Lawrence Livermore National Laboratory (LLNL) and Arizona State University (ASU) received the Best Paper Honorable Mention Award at WACV 2021 for their paper "Generative Patch Priors for Practical Compressive Image Recovery".

      The paper proposes a novel model of natural images as a composition of small patches which are obtained from a deep generative network. This is unlike prior approaches where the networks attempt to model image-level distributions and are unable to generalize outside training distributions. The key idea in this paper is that learning patch-level statistics is far easier. As the authors demonstrate, this model can then be used to efficiently solve challenging inverse problems in imaging such as compressive image recovery and inpainting even from very few measurements for diverse natural scenes.
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  •  AWARD    Outstanding Presentation Award at the 28th Conference of Information Processing Society of Japan/Consumer Device & Systems
    Date: October 20, 2020
    Awarded to: Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik, Hiroshi Mineno
    MERL Contacts: Jianlin Guo; Philip V. Orlik
    Research Areas: Communications, Optimization, Signal Processing
    Brief
    • MELCO and MERL researchers have won "Outstanding Presentation Award" at 28th Conference of Information Processing Society of Japan (IPSJ)/Consumer Device & Systems held on September 29-30, 2020. The paper titled "IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1 GHz Frequency Bands" reports IEEE 802.19.3 standard development on coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. MERL and MELCO have been leading this standard development and made major technical contributions, which propose methods to mitigate interference in smart meter systems. The authors are Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik and Hiroshi Mineno.
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  •  AWARD    Best Poster Award and Best Video Award at the International Society for Music Information Retrieval Conference (ISMIR) 2020
    Date: October 15, 2020
    Awarded to: Ethan Manilow, Gordon Wichern, Jonathan Le Roux
    MERL Contacts: Jonathan Le Roux; Gordon Wichern
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    Brief
    • Former MERL intern Ethan Manilow and MERL researchers Gordon Wichern and Jonathan Le Roux won Best Poster Award and Best Video Award at the 2020 International Society for Music Information Retrieval Conference (ISMIR 2020) for the paper "Hierarchical Musical Source Separation". The conference was held October 11-14 in a virtual format. The Best Poster Awards and Best Video Awards were awarded by popular vote among the conference attendees.

      The paper proposes a new method for isolating individual sounds in an audio mixture that accounts for the hierarchical relationship between sound sources. Many sounds we are interested in analyzing are hierarchical in nature, e.g., during a music performance, a hi-hat note is one of many such hi-hat notes, which is one of several parts of a drumkit, itself one of many instruments in a band, which might be playing in a bar with other sounds occurring. Inspired by this, the paper re-frames the audio source separation problem as hierarchical, combining similar sounds together at certain levels while separating them at other levels, and shows on a musical instrument separation task that a hierarchical approach outperforms non-hierarchical models while also requiring less training data. The paper, poster, and video can be seen on the paper page on the ISMIR website.
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  •  AWARD    Best Paper AWARD at International Workshop on Informatics (IWIN) 2020
    Date: September 11, 2020
    Awarded to: Yukimasa Nagai, Jianlin Guo, Takenori Sumi, Philip Orlik, Hiroshi Mineno
    MERL Contact: Jianlin Guo
    Research Areas: Communications, Signal Processing
    Brief
    • MELCO and MERL researchers have won one of two Best Paper Awards at International Workshop on Informatics (IWIN) 2020. The paper titled 'Hybrid CSMA/CA for Sub-1 GHz Frequency Band Coexistence of IEEE 802.11ah and IEEE 802.15.4g', reports research on the severity of interference between IEEE 802.11ah and IEEE 802.15.4g based networks and also proposes methods to mitigate this interference in smart meter systems. This research reported in this paper has also informed several of MELCO/MERL's contributions to the IEEE P802.19.3 task group which is developing standards to allow for improved coexistence in outdoor metering systems. Authors are Yukimasa Nagai, Jianlin Guo, Takenori Sumi, Philip Orlik and Hiroshi Mineno.
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  •  AWARD    Best Student Paper Award at the IEEE Conference on Control Technology and Applications
    Date: August 26, 2020
    Awarded to: Marcus Greiff, Anders Robertsson, Karl Berntorp
    MERL Contacts: Karl Berntorp; Marcus Greiff
    Research Areas: Control, Signal Processing
    Brief
    • Marcus Greiff, a former MERL intern from the Department of Automatic Control, Lund University, Sweden, won one of three 2020 CCTA Outstanding Student Paper Awards and the Best Student Paper Award at the 2020 IEEE Conference on Control Technology and Applications. The research leading up to the awarded paper titled 'MSE-Optimal Measurement Dimension Reduction in Gaussian Filtering', concerned how to select a reduced set of measurements in estimation applications while minimally degrading performance, was done in collaboration with Karl Berntorp at MERL.
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  •  AWARD    Best conference paper of IEEE PES-GM 2020
    Date: June 18, 2020
    Awarded to: Tong Huang, Hongbo Sun, K.J. Kim, Daniel Nikovski, Le Xie
    MERL Contacts: Kyeong Jin (K.J.) Kim; Daniel N. Nikovski; Hongbo Sun
    Research Areas: Data Analytics, Electric Systems, Optimization
    Brief
    • A paper on A Holistic Framework for Parameter Coordination of Interconnected Microgrids Against Natural Disasters, written by Tong Huang, a former MERL intern from Texas A&M University, has been selected as one of the Best Conference Papers at the 2020 Power and Energy Society General Meeting (PES-GM). IEEE PES-GM is the flagship conference for the IEEE Power and Energy Society. The work was done in collaboration with Hongbo Sun, K. J. Kim, and Daniel Nikovski from MERL, and Tong's advisor, Prof. Le Xie from Texas A&M University.
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  •  AWARD    Best Paper Award at the IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) 2019
    Date: December 18, 2019
    Awarded to: Xuankai Chang, Wangyou Zhang, Yanmin Qian, Jonathan Le Roux, Shinji Watanabe
    MERL Contact: Jonathan Le Roux
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    Brief
    • MERL researcher Jonathan Le Roux and co-authors Xuankai Chang, Shinji Watanabe (Johns Hopkins University), Wangyou Zhang, and Yanmin Qian (Shanghai Jiao Tong University) won the Best Paper Award at the 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2019), for the paper "MIMO-Speech: End-to-End Multi-Channel Multi-Speaker Speech Recognition". MIMO-Speech is a fully neural end-to-end framework that can transcribe the text of multiple speakers speaking simultaneously from multi-channel input. The system is comprised of a monaural masking network, a multi-source neural beamformer, and a multi-output speech recognition model, which are jointly optimized only via an automatic speech recognition (ASR) criterion. The award was received by lead author Xuankai Chang during the conference, which was held in Sentosa, Singapore from December 14-18, 2019.
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  •  AWARD    MERL Receives Cultural Vista's 2019 Global Partnership Award
    Date: October 17, 2019
    Awarded to: Mitsubishi Electric Research Labs
    MERL Contact: Elizabeth Phillips
    Brief
    • MERL received Cultural Vista's Global Partnership Award at the 2019 Cultural Vistas Awards Gala (#CVGala)in NYC in October. This event brought together more than 250 leaders from across the business, education, government, and diplomatic communities for a special evening recognizing leadership in advancing global skills and understanding.

      The Global Partnership award recognizes MERL's exemplary contributions to advancing friendship, understanding, and effective collaboration between the United States and Japan.
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  •  AWARD    MERL Researchers win Best Paper Award at ICCV 2019 Workshop on Statistical Deep Learning in Computer Vision
    Date: October 27, 2019
    Awarded to: Abhinav Kumar, Tim K. Marks, Wenxuan Mou, Chen Feng, Xiaoming Liu
    MERL Contact: Tim K. Marks
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • MERL researcher Tim Marks, former MERL interns Abhinav Kumar and Wenxuan Mou, and MERL consultants Professor Chen Feng (NYU) and Professor Xiaoming Liu (MSU) received the Best Oral Paper Award at the IEEE/CVF International Conference on Computer Vision (ICCV) 2019 Workshop on Statistical Deep Learning in Computer Vision (SDL-CV) held in Seoul, Korea. Their paper, entitled "UGLLI Face Alignment: Estimating Uncertainty with Gaussian Log-Likelihood Loss," describes a method which, given an image of a face, estimates not only the locations of facial landmarks but also the uncertainty of each landmark location estimate.
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  •  AWARD    MERL Researcher Devesh Jha Wins the Rudolf Kalman Best Paper Award 2019
    Date: October 10, 2019
    Awarded to: Devesh Jha, Nurali Virani, Zhenyuan Yuan, Ishana Shekhawat and Asok Ray
    MERL Contact: Devesh K. Jha
    Research Areas: Artificial Intelligence, Control, Data Analytics, Machine Learning, Robotics
    Brief
    • MERL researcher Devesh Jha has won the Rudolf Kalman Best Paper Award 2019 for the paper entitled "Imitation of Demonstrations Using Bayesian Filtering With Nonparametric Data-Driven Models". This paper, published in a Special Commemorative Issue for Rudolf E. Kalman in the ASME JDSMC in March 2018, uses Bayesian filtering for imitation learning in Hidden Mode Hybrid Systems. This award is given annually by the Dynamic Systems and Control Division of ASME to the authors of the best paper published in the ASME Journal of Dynamic Systems Measurement and Control during the preceding year.
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  •  AWARD    MERL Researchers Won IEEE ICC Best Paper Award
    Date: May 22, 2019
    Awarded to: Siriramya Bhamidipati, Kyeong Jin Kim, Hongbo Sun, Philip Orlik
    MERL Contacts: Kyeong Jin (K.J.) Kim; Hongbo Sun
    Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal Processing, Information Security
    Brief
    • MERL researchers, Kyeong Jin Kim, Hongbo Sun, Philip Orlik, along with lead author and former MERL intern Siriramya Bhamidipati were awarded the Smart Grid Symposium Best Paper Award at this year's International Conference on Communications (ICC) held in Shanghai, China. There paper titled "GPS Spoofing Detection and Mitigation in PMUs Using Distributed Multiple Directional Antennas," described a technique to rapidly detect and mitigate GPS timing attacks/errors via hardware (antennas) and signal processing (Kalman Filtering).
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  •  AWARD    MERL researcher wins IEEE Young Author Best Paper award
    Date: January 2, 2019
    Awarded to: Siheng Chen
    Research Area: Signal Processing
    Brief
    • MERL researcher, Siheng Chen, has won an IEEE Young Author Best Paper award for his paper entitled "Discrete Signal Processing on Graphs: Sampling Theory". This paper, published in the December 2015 issue of IEEE Transactions on Signal Processing, proposes a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory and shows that perfect recovery is possible for graph signals bandlimited under the graph Fourier transform. The award honors the authors of an especially meritorious paper dealing with a subject related to IEEE's technical scope and appearing in one if its journals within a three year window of eligibility.
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  •  AWARD    MERL researcher wins Best Visualization Note Award at PacificVis2019 Conference
    Date: April 23, 2019
    Awarded to: Teng-yok Lee
    Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Machine Learning
    Brief
    • MERL researcher Teng-yok Lee has won the Best Visualization Note Award at the PacificVis 2019 conference held in Bangkok Thailand, from April 23-26, 2019. The paper entitled "Space-Time Slicing: Visualizing Object Detector Performance in Driving Video Sequences" presents a visualization method called Space-Time Slicing to assist a human developer in the development of object detectors for driving applications without requiring labeled data. Space-Time Slicing reveals patterns in the detection data that can suggest the presence of false positives and false negatives.
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  •  AWARD    Former Intern Receives IBM Scientific Award Honorable Mention
    Date: January 16, 2019
    Awarded to: Daniel Dinis
    MERL Contact: Rui Ma
    Research Areas: Communications, Signal Processing
    Brief
    • Former MERL intern Daniel Dinis from University of Aveiro (UA), Portugal has received the 2018 IBM Scientific Award with Honorable Mention referring to the contributions on "Real-time Tunable Delta-sigma modulators for All-Digital RF Transmitters" in his Ph.D. study.

      The award-winning work includes research conducted under the supervision of Arnaldo Oliveira and José Neto Vieira, professors from the Department of Electronics and Information Technology (DETI) of the UA, as well as contributions made during Daniel's 7 month internship in 2017 at MERL.

      The ceremony for the presentation of the 28th IBM Scientific Prize took on January 16th, at the Noble Hall of the Superior Technical Institute. It was chaired by Marcelo Rebelo de Sousa, President of the Portuguese Republic.
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  •  AWARD    R&D100 award for Deep Learning-based Water Detector
    Date: November 16, 2018
    Awarded to: Ziming Zhang, Alan Sullivan, Hideaki Maehara, Kenji Taira, Kazuo Sugimoto
    MERL Contact: Alan Sullivan
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • Researchers and developers from MERL, Mitsubishi Electric and Mitsubishi Electric Engineering (MEE) have been recognized with an R&D100 award for the development of a deep learning-based water detector. Automatic detection of water levels in rivers and streams is critical for early warning of flash flooding. Existing systems require a height gauge be placed in the river or stream, something that is costly and sometimes impossible. The new deep learning-based water detector uses only images from a video camera along with 3D measurements of the river valley to determine water levels and warn of potential flooding. The system is robust to lighting and weather conditions working well during the night as well as during fog or rain. Deep learning is a relatively new technique that uses neural networks and AI that are trained from real data to perform human-level recognition tasks. This work is powered by Mitsubishi Electric's Maisart AI technology.
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  •  AWARD    Best Student Paper Award at IEEE ICASSP 2018
    Date: April 17, 2018
    Awarded to: Zhong-Qiu Wang
    MERL Contact: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • Former MERL intern Zhong-Qiu Wang (Ph.D. Candidate at Ohio State University) has received a Best Student Paper Award at the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018) for the paper "Multi-Channel Deep Clustering: Discriminative Spectral and Spatial Embeddings for Speaker-Independent Speech Separation" by Zhong-Qiu Wang, Jonathan Le Roux, and John Hershey. The paper presents work performed during Zhong-Qiu's internship at MERL in the summer 2017, extending MERL's pioneering Deep Clustering framework for speech separation to a multi-channel setup. The award was received on behalf on Zhong-Qiu by MERL researcher and co-author Jonathan Le Roux during the conference, held in Calgary April 15-20.
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  •  AWARD    Best Student Paper Award at the International Conference on Data Mining
    Date: November 30, 2017
    Awarded to: Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn Keogh
    MERL Contact: Daniel N. Nikovski
    Research Area: Data Analytics
    Brief
    • Yan Zhu, a former MERL intern from the University of California at Riverside has won the Best Student Paper Award at the International Conference on Data Mining in 2017, for her work on time series chains, a novel primitive for time series analysis. The work was done in collaboration with Makoto Imamura, formerly at Information Technology Center/AI Department, and currently a professor at Tokai University in Tokyo, Japan, Daniel Nikovski from MERL, and Yan's advisor, Prof. Eamonn Keogh from UC Riverside, whose lab has had a long and fruitful collaboration with MERL and Mitsubishi Electric.
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