News & Events

93 were found.




  •  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 Contacts: Alan Sullivan; Ziming Zhang
    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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  •  NEWS   MERL Researchers Demonstrate Robot Learning Technology at CEATEC'18
    Date: October 15, 2018 - October 19, 2018
    Where: CEATEC'18, Makuhari Messe, Tokyo
    MERL Contacts: Devesh Jha; Daniel Nikovski; Diego Romeres; Alan Sullivan; Jeroen van Baar; William Yerazunis
    Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Robotics
    Brief
    • MERL's work on robot learning algorithms was demonstrated at CEATEC'18, Japan's largest IT and electronics exhibition and conference held annually at Makuhari Messe near Tokyo. A team of researchers from the Data Analytics Group at MERL and the Artificial Intelligence Department of the Information Technology Center (ITC) of MELCO presented an interactive demonstration of a model-based artificial intelligence algorithm that learns how to control equipment autonomously. The algorithm developed at MERL constructs models of mechanical equipment through repeated trial and error, and then learns control policies based on these models. The demonstration used a circular maze, where the objective is to drive a ball to the center of the maze by tipping and tilting the maze, a task that is difficult even for humans; approximately half of the CEATEC'18 visitors who tried to steer the ball by means of a joystick could not bring it to the center of the maze within one minute. In contrast, MERL's algorithm successfully learned how to drive the ball to the goal within ten seconds without the need for human programming. The demo was at the entrance of MELCO's booth at CEATEC'18, inviting visitors to learn more about MELCO's many other AI technologies on display, and was seen by an estimated more than 50,000 visitors over the five days of the expo.
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  •  EVENT   MERL is a Proud Sponsor of the Grace Hopper Celebration 2018!
    Date: Wednesday, September 26, 2018 - Friday, September 28, 2018
    MERL Contacts: Chiori Hori; Elizabeth Phillips
    Location: Houston, Texas
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • "MERL, in partnership with Mitsubishi Electric was a Gold Sponsor of the Grace Hopper Celebration 2018 (GHC18) held in Houston, TX on September 26-28th. Presented by AnitaB.org and the Association for Computing Machinery, this is world's largest gathering of women technologists. Chiori Hori and Elizabeth Phillips from MERL, and Yoshiyuki Umei, Jared Baker and Lien Randle from MEUS, proudly represented Mitsubishi Electric at the recruiting expo, that drew over 20,000 female technologists this year.
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  •  EVENT   MERL 3rd Annual Open House
    Date & Time: Thursday, November 29, 2018; 4-6pm
    MERL Contacts: Marissa Deegan; Elizabeth Phillips; Jeroen van Baar; Anthony Vetro
    Location: 201 Broadway, 8th floor, Cambridge, MA
    Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio
    Brief
    • Snacks, demos, science: On Thursday 11/29, Mitsubishi Electric Research Labs (MERL) will host an open house for graduate+ students interested in internships, post-docs, and research scientist positions. The event will be held from 4-6pm and will feature demos & short presentations in our main areas of research including artificial intelligence, robotics, computer vision, speech processing, optimization, machine learning, data analytics, signal processing, communications, sensing, control and dynamical systems, as well as multi-physyical modeling and electronic devices. MERL is a high impact publication-oriented research lab with very extensive internship and university collaboration programs. Most internships lead to publication; many of our interns and staff have gone on to notable careers at MERL and in academia. Come mix with our researchers, see our state of the art technologies, and learn about our research opportunities. Dress code: casual, with resumes.

      Pre-registration for the event is strongly encouraged:
      merlopenhouse.eventbrite.com

      Current internship and employment openings:
      www.merl.com/internship/openings
      www.merl.com/employment/employment

      Information about working at MERL:
      www.merl.com/employment
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  •  NEWS   Scene interpretation results of SA group members are listed as the leader of benchmark competition
    Date: July 13, 2015 - July 17, 2015
    MERL Contact: Jay Thornton
    Research Area: Machine Learning
    Brief
    • SA group members (M. Liu, S. Lin (intern), S. Ramalingam, O. Tuzel) presented a paper at the Robotics Science and Systems Conference in Rome July 13-17 called 'Layered Interpretation of Street View Images'. The results they reported are now listed as the leader of the benchmark competition sponsored by Daimler. [Note that at that URL ref 2 is from collaboration with Daimler and it uses a FPGA for high speed, whereas MERL result is obtained with desktop computer and GPU.]
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  •  NEWS   Nikkei reports on Mitsubishi Electric speech recognition
    Date: April 20, 2015
    Brief
    • Mitsubishi Electric researcher, Yuuki Tachioka of Japan, and MERL researcher, Shinji Watanabe, presented a paper at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP) entitled, "A Discriminative Method for Recurrent Neural Network Language Models". This paper describes a discriminative (language modelling) method for Japanese speech recognition. The Japanese Nikkei newspapers and some other press outlets reported on this method and its performance for Japanese speech recognition tasks.
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  •  NEWS   Second Place in REVERB Challenge
    Date: May 10, 2014
    Where: REVERB Workshop
    Research Area: Speech & Audio
    Brief
    • Mitsubishi Electric's submission to the REVERB workshop achieved the second best performance among all participating institutes. The team included Yuuki Tachioka and Tomohiro Narita of MELCO in Japan, and Shinji Watanabe and Felix Weninger of MERL. The challenge addresses automatic speech recognition systems that are robust against varying room acoustics.
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  •  NEWS   International Workshop on Machine Listening in Multisource Environments (CHiME) 2013: publication by Jonathan Le Roux, John R. Hershey, Shinji Watanabe and others
    Date: June 1, 2013
    Where: International Workshop on Machine Listening in Multisource Environments (CHiME)
    MERL Contact: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • The paper "Discriminative Methods for Noise Robust Speech Recognition: A CHiME Challenge Benchmark" by Tachioka, Y., Watanabe, S., Le Roux, J. and Hershey, J.R. was presented at the International Workshop on Machine Listening in Multisource Environments (CHiME)
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  •  AWARD   CHiME 2012 Speech Separation and Recognition Challenge Best Performance
    Date: June 1, 2013
    Awarded to: Yuuki Tachioka, Shinji Watanabe, Jonathan Le Roux and John R. Hershey
    Awarded for: "Discriminative Methods for Noise Robust Speech Recognition: A CHiME Challenge Benchmark"
    Awarded by: International Workshop on Machine Listening in Multisource Environments (CHiME)
    MERL Contact: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • The results of the 2nd 'CHiME' Speech Separation and Recognition Challenge are out! The team formed by MELCO researcher Yuuki Tachioka and MERL Speech & Audio team researchers Shinji Watanabe, Jonathan Le Roux and John Hershey obtained the best results in the continuous speech recognition task (Track 2). This very challenging task consisted in recognizing speech corrupted by highly non-stationary noises recorded in a real living room. Our proposal, which also included a simple yet extremely efficient denoising front-end, focused on investigating and developing state-of-the-art automatic speech recognition back-end techniques: feature transformation methods, as well as discriminative training methods for acoustic and language modeling. Our system significantly outperformed other participants. Our code has since been released as an improved baseline for the community to use.
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  •  NEWS   ICLR 2013: publication by Jonathan Le Roux and others
    Date: May 2, 2013
    Where: International Conference on Learning Representations (ICLR)
    MERL Contact: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • The paper "Block Coordinate Descent for Sparse NMF" by Potluru, V.K., Plis, S.M., Le Roux, J., Pearlmutter, B.A., Calhoun, V.D. and Hayes, T.P. was presented at the International Conference on Learning Representations (ICLR)
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  •  NEWS   ICMLA 2012: publication by MERL researchers and others
    Date: December 12, 2012
    Where: International Conference on Machine Learning and Applications (ICMLA)
    Research Area: Machine Learning
    Brief
    • The paper "Compressive Clustering of High-Dimensional Data" by Ruta, A. and Porikli, F. was presented at the International Conference on Machine Learning and Applications (ICMLA)
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  •  NEWS   APSIPA Transactions on Signal and Information Processing: publication by Shinji Watanabe and others
    Date: December 6, 2012
    Where: APSIPA Transactions on Signal and Information Processing
    Research Area: Speech & Audio
    Brief
    • The article "Bayesian Approaches to Acoustic Modeling: A Review" by Watanabe, S. and Nakamura, A. was published in APSIPA Transactions on Signal and Information Processing
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  •  NEWS   Techniques for Noise Robustness in Automatic Speech Recognition: publication by Jonathan Le Roux, John R. Hershey and others
    Date: November 28, 2012
    Where: Techniques for Noise Robustness in Automatic Speech Recognition
    MERL Contact: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • The article "Factorial Models for Noise Robust Speech Recognition" by Hershey, J.R., Rennie, S.J. and Le Roux, J. was published in the book Techniques for Noise Robustness in Automatic Speech Recognition
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  •  NEWS   IEEE Signal Processing Magazine: publication by Shinji Watanabe and others
    Date: November 1, 2012
    Where: IEEE Signal Processing Magazine
    Research Area: Speech & Audio
    Brief
    • The article "Structured Discriminative Models For Speech Recognition" by Gales, M., Watanabe, S. and Fosler-Lussier, E. was published in IEEE Signal Processing Magazine
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  •  NEWS   HFES 2012: publication by Bret A. Harsham and others
    Date: October 22, 2012
    Where: Annual Meeting of the Human Factors and Ergonomics Society (HFES)
    MERL Contact: Bret Harsham
    Research Area: Speech & Audio
    Brief
    • The paper "Evaluation of Two Types of In-Vehicle Music Retrieval and Navigation Systems" by Zhang, J., Borowsky, A., Schmidt-Nielsen, B., Harsham, B., Weinberg, G., Romoser, M.R.E. and Fisher, D.L. was presented at the Annual Meeting of the Human Factors and Ergonomics Society (HFES)
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  •  NEWS   3DIMPVT 2012: publication by Ming-Yu Liu and others
    Date: October 13, 2012
    Where: IEEE International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)
    Research Area: Machine Learning
    Brief
    • The paper "Classification and Pose Estimation of Vehicles in Videos by 3D Modeling within Discrete-Continuous Optimization" by Hodlmoser, M., Micusik, B., Liu, M.-Y., Pollefeys, M. and Kaampel, M. was presented at the IEEE International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)
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  •  NEWS   ICEIS 2012: publication by Alan W. Esenther, Daniel N. Nikovski and others
    Date: June 28, 2012
    Where: International Conference on Enterprise Information Systems (ICEIS)
    MERL Contact: Daniel Nikovski
    Research Area: Data Analytics
    Brief
    • The paper "Bayesian Networks for Matcher Composition in Automatic Schema Matching" by Nikovski, D., Esenther, A., Ye, X., Shiba, M. and Takayama, S. was presented at the International Conference on Enterprise Information Systems (ICEIS)
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  •  NEWS   IWSML 2012: publication by Jonathan Le Roux, John R. Hershey and others
    Date: March 31, 2012
    Where: International Workshop on Statistical Machine Learning for Speech Processing (IWSML)
    MERL Contact: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • The paper "Latent Dirichlet Reallocation for Term Swapping" by Heaukulani, C., Le Roux, J. and Hershey, J.R. was presented at the International Workshop on Statistical Machine Learning for Speech Processing (IWSML)
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  •  NEWS   ASJ 2012: publication by Jonathan Le Roux and John R. Hershey
    Date: March 13, 2012
    Where: Acoustical Society of Japan Spring Meeting (ASJ)
    MERL Contact: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • The paper "Speech Enhancement by Indirect VTS" by Le Roux, J. and Hershey, J.R. was presented at the Acoustical Society of Japan Spring Meeting (ASJ)
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  •  NEWS   IEEE Transactions on Pattern Analysis and Machine Intelligence: publication by MERL researchers and others
    Date: January 10, 2012
    Where: IEEE Transactions on Pattern Analysis and Machine Intelligence
    Research Area: Machine Learning
    Brief
    • The article "Scalable Active Learning for Multi-Class Image Classification" by Joshi, A.J., Porikli, F. and Papanikolopoulos, N. was published in IEEE Transactions on Pattern Analysis and Machine Intelligence
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