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Audio and Acoustic Signal Processing

DEEP LEARNING ARCHITECTURE FOR PEDESTRIAN 3-D LOCALIZATION AND TRACKING USING MULTIPLE CAMERAS

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Authors:
Byeongho Heo, Moonsub Byeon, Jin Young Choi
Submitted On:
15 September 2017 - 11:10pm
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icip2017_2dpgp_kkk_upload.pptx

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[1] Byeongho Heo, Moonsub Byeon, Jin Young Choi, " DEEP LEARNING ARCHITECTURE FOR PEDESTRIAN 3-D LOCALIZATION AND TRACKING USING MULTIPLE CAMERAS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2167. Accessed: Nov. 23, 2017.
@article{2167-17,
url = {http://sigport.org/2167},
author = {Byeongho Heo; Moonsub Byeon; Jin Young Choi },
publisher = {IEEE SigPort},
title = { DEEP LEARNING ARCHITECTURE FOR PEDESTRIAN 3-D LOCALIZATION AND TRACKING USING MULTIPLE CAMERAS},
year = {2017} }
TY - EJOUR
T1 - DEEP LEARNING ARCHITECTURE FOR PEDESTRIAN 3-D LOCALIZATION AND TRACKING USING MULTIPLE CAMERAS
AU - Byeongho Heo; Moonsub Byeon; Jin Young Choi
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2167
ER -
Byeongho Heo, Moonsub Byeon, Jin Young Choi. (2017). DEEP LEARNING ARCHITECTURE FOR PEDESTRIAN 3-D LOCALIZATION AND TRACKING USING MULTIPLE CAMERAS. IEEE SigPort. http://sigport.org/2167
Byeongho Heo, Moonsub Byeon, Jin Young Choi, 2017. DEEP LEARNING ARCHITECTURE FOR PEDESTRIAN 3-D LOCALIZATION AND TRACKING USING MULTIPLE CAMERAS. Available at: http://sigport.org/2167.
Byeongho Heo, Moonsub Byeon, Jin Young Choi. (2017). " DEEP LEARNING ARCHITECTURE FOR PEDESTRIAN 3-D LOCALIZATION AND TRACKING USING MULTIPLE CAMERAS." Web.
1. Byeongho Heo, Moonsub Byeon, Jin Young Choi. DEEP LEARNING ARCHITECTURE FOR PEDESTRIAN 3-D LOCALIZATION AND TRACKING USING MULTIPLE CAMERAS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2167

MODELING STRUCTURAL DISSIMILARITY BASED ON SHAPE EMBODIMENT FOR CELL SEGMENTATION


Accurate cell segmentation is one of the critical, yet challenging problems in microscopy images due to ambiguous boundaries as well as a wide variation of shapes and sizes of cells. Even though a number of existing methods have achieved decent results for cell segmentation, boundary vagueness between adjoining cells tended to cause generation of perceptually inaccurate segmentation of stained nuclei. We propose

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15 September 2017 - 1:46am
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[1] , "MODELING STRUCTURAL DISSIMILARITY BASED ON SHAPE EMBODIMENT FOR CELL SEGMENTATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2084. Accessed: Nov. 23, 2017.
@article{2084-17,
url = {http://sigport.org/2084},
author = { },
publisher = {IEEE SigPort},
title = {MODELING STRUCTURAL DISSIMILARITY BASED ON SHAPE EMBODIMENT FOR CELL SEGMENTATION},
year = {2017} }
TY - EJOUR
T1 - MODELING STRUCTURAL DISSIMILARITY BASED ON SHAPE EMBODIMENT FOR CELL SEGMENTATION
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2084
ER -
. (2017). MODELING STRUCTURAL DISSIMILARITY BASED ON SHAPE EMBODIMENT FOR CELL SEGMENTATION. IEEE SigPort. http://sigport.org/2084
, 2017. MODELING STRUCTURAL DISSIMILARITY BASED ON SHAPE EMBODIMENT FOR CELL SEGMENTATION. Available at: http://sigport.org/2084.
. (2017). "MODELING STRUCTURAL DISSIMILARITY BASED ON SHAPE EMBODIMENT FOR CELL SEGMENTATION." Web.
1. . MODELING STRUCTURAL DISSIMILARITY BASED ON SHAPE EMBODIMENT FOR CELL SEGMENTATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2084

MOTION-CONSISTENT VIDEO INPAINTING


This demonstration aims to show some resulting videos for our method presented in ICIP. It is a fast and automatic inpainting technique for high-definition videos which works under many challenging conditions such as a moving camera, a dynamic background or a long-lasting occlusion. By incorporating optical flow in a global patch-based algorithm, our method provide improvements compared to the state-of-the-art, especially in motion preservation.

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Authors:
Andres Almansa, Yann Gousseau, Simon Masnou
Submitted On:
14 September 2017 - 5:32pm
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Poster_ThucTrinhLE_videoinpainting_ICIP.pdf

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[1] Andres Almansa, Yann Gousseau, Simon Masnou, "MOTION-CONSISTENT VIDEO INPAINTING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2051. Accessed: Nov. 23, 2017.
@article{2051-17,
url = {http://sigport.org/2051},
author = {Andres Almansa; Yann Gousseau; Simon Masnou },
publisher = {IEEE SigPort},
title = {MOTION-CONSISTENT VIDEO INPAINTING},
year = {2017} }
TY - EJOUR
T1 - MOTION-CONSISTENT VIDEO INPAINTING
AU - Andres Almansa; Yann Gousseau; Simon Masnou
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2051
ER -
Andres Almansa, Yann Gousseau, Simon Masnou. (2017). MOTION-CONSISTENT VIDEO INPAINTING. IEEE SigPort. http://sigport.org/2051
Andres Almansa, Yann Gousseau, Simon Masnou, 2017. MOTION-CONSISTENT VIDEO INPAINTING. Available at: http://sigport.org/2051.
Andres Almansa, Yann Gousseau, Simon Masnou. (2017). "MOTION-CONSISTENT VIDEO INPAINTING." Web.
1. Andres Almansa, Yann Gousseau, Simon Masnou. MOTION-CONSISTENT VIDEO INPAINTING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2051

GLOBAL MULTIVIEW REGISTRATION USING NON-CONVEX ADMM


We consider the problem of aligning multiview scans obtained using
a range scanner. The computational pipeline for this problem can be
divided into two phases: (i) finding point-to-point correspondences
between overlapping scans, and (ii) registration of the scans based
on the found correspondences. The focus of this work is on global
registration in which the scans (modeled as point clouds) are required
to be jointly registered in a common reference frame. We consider
an optimization framework for global registration that is based on

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Authors:
Kunal N. Chaudhury
Submitted On:
14 September 2017 - 7:08am
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slides.pdf

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[1] Kunal N. Chaudhury, "GLOBAL MULTIVIEW REGISTRATION USING NON-CONVEX ADMM", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2015. Accessed: Nov. 23, 2017.
@article{2015-17,
url = {http://sigport.org/2015},
author = {Kunal N. Chaudhury },
publisher = {IEEE SigPort},
title = {GLOBAL MULTIVIEW REGISTRATION USING NON-CONVEX ADMM},
year = {2017} }
TY - EJOUR
T1 - GLOBAL MULTIVIEW REGISTRATION USING NON-CONVEX ADMM
AU - Kunal N. Chaudhury
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2015
ER -
Kunal N. Chaudhury. (2017). GLOBAL MULTIVIEW REGISTRATION USING NON-CONVEX ADMM. IEEE SigPort. http://sigport.org/2015
Kunal N. Chaudhury, 2017. GLOBAL MULTIVIEW REGISTRATION USING NON-CONVEX ADMM. Available at: http://sigport.org/2015.
Kunal N. Chaudhury. (2017). "GLOBAL MULTIVIEW REGISTRATION USING NON-CONVEX ADMM." Web.
1. Kunal N. Chaudhury. GLOBAL MULTIVIEW REGISTRATION USING NON-CONVEX ADMM [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2015

UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION


Unsupervised feature selection has been proven to be an efficient technique in mitigating the curse of dimensionality. It helps to understand and analyze the prevalent high-dimensional unlabeled data. Recently, based on the self-similarity property of objects, self-representation which assumes that a feature can be represented by the linear combination of its relevant features has been successfully used in unsupervised feature selection. In this paper, we propose a novel algorithm termed Manifold Regularized Selfrepresentation(MRSR) based on the self-representation ability of features.

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Authors:
Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang
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13 September 2017 - 12:13am
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MRSR_ICIP_1266

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[1] Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang, "UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1958. Accessed: Nov. 23, 2017.
@article{1958-17,
url = {http://sigport.org/1958},
author = {Siqi Liang; Pengfei Zhu; Qinghua Hu; Chongqing Zhang },
publisher = {IEEE SigPort},
title = {UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION},
year = {2017} }
TY - EJOUR
T1 - UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION
AU - Siqi Liang; Pengfei Zhu; Qinghua Hu; Chongqing Zhang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1958
ER -
Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang. (2017). UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION. IEEE SigPort. http://sigport.org/1958
Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang, 2017. UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION. Available at: http://sigport.org/1958.
Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang. (2017). "UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION." Web.
1. Siqi Liang, Pengfei Zhu, Qinghua Hu, Chongqing Zhang. UNSUPERVISED FEATURE SELECTION BY MANIFOLD REGULARIZED SELF-REPRESENTATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1958

V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER)


A major drawback of JPEG 2000 is the computational complexity of its entropy coder named Embedded Block Coder with Optimized Truncation (EBCOT). This paper proposes two alterations to the original algorithm that seek to improve the trade-off between compression efficiency and throughput. Firstly, magnitude bits within a bit plane are not prioritized by their significance anymore, but instead coded in a single pass instead of three, reducing the amount of expensive memory accesses at the cost of fewer truncation points.

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Authors:
Volker Bruns, Miguel Á. Martínez-del-Amor, Heiko Sparenberg
Submitted On:
12 September 2017 - 5:00am
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V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER).pdf

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[1] Volker Bruns, Miguel Á. Martínez-del-Amor, Heiko Sparenberg, "V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER)", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1930. Accessed: Nov. 23, 2017.
@article{1930-17,
url = {http://sigport.org/1930},
author = {Volker Bruns; Miguel Á. Martínez-del-Amor; Heiko Sparenberg },
publisher = {IEEE SigPort},
title = {V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER)},
year = {2017} }
TY - EJOUR
T1 - V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER)
AU - Volker Bruns; Miguel Á. Martínez-del-Amor; Heiko Sparenberg
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1930
ER -
Volker Bruns, Miguel Á. Martínez-del-Amor, Heiko Sparenberg. (2017). V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER). IEEE SigPort. http://sigport.org/1930
Volker Bruns, Miguel Á. Martínez-del-Amor, Heiko Sparenberg, 2017. V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER). Available at: http://sigport.org/1930.
Volker Bruns, Miguel Á. Martínez-del-Amor, Heiko Sparenberg. (2017). "V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER)." Web.
1. Volker Bruns, Miguel Á. Martínez-del-Amor, Heiko Sparenberg. V. Bruns, M.A. Martinez-del-Amor, H. Sparenberg - GPU-friendly EBCOT variant with single-pass scan order and raw bit plane coding (POSTER) [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1930

Water Surface Reconstruction and Truly Random Numbers Generation From Images of Wind-Generated Gravity Waves


We present an image-based approach to generate truly random numbers from the surface of water bodies such as oceanic bays. As a natural phenomenon, wind-generated gravity waves have non-deterministic behavior. We use the randomness of the angular relation between pairs of estimated surface normals to generate uniformly distributed random binary digits and build random numbers from those digits. Our approach produces compelling geometric models of water surfaces and generates random numbers with high entropy.

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Authors:
Gustavo Marques Netto
Submitted On:
4 September 2017 - 9:12pm
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Poster

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[1] Gustavo Marques Netto, "Water Surface Reconstruction and Truly Random Numbers Generation From Images of Wind-Generated Gravity Waves", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1828. Accessed: Nov. 23, 2017.
@article{1828-17,
url = {http://sigport.org/1828},
author = {Gustavo Marques Netto },
publisher = {IEEE SigPort},
title = {Water Surface Reconstruction and Truly Random Numbers Generation From Images of Wind-Generated Gravity Waves},
year = {2017} }
TY - EJOUR
T1 - Water Surface Reconstruction and Truly Random Numbers Generation From Images of Wind-Generated Gravity Waves
AU - Gustavo Marques Netto
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1828
ER -
Gustavo Marques Netto. (2017). Water Surface Reconstruction and Truly Random Numbers Generation From Images of Wind-Generated Gravity Waves. IEEE SigPort. http://sigport.org/1828
Gustavo Marques Netto, 2017. Water Surface Reconstruction and Truly Random Numbers Generation From Images of Wind-Generated Gravity Waves. Available at: http://sigport.org/1828.
Gustavo Marques Netto. (2017). "Water Surface Reconstruction and Truly Random Numbers Generation From Images of Wind-Generated Gravity Waves." Web.
1. Gustavo Marques Netto. Water Surface Reconstruction and Truly Random Numbers Generation From Images of Wind-Generated Gravity Waves [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1828

SALIENCE BASED LEXICAL FEATURES FOR EMOTION RECOGNITION


In this paper we focus on the usefulness of verbal events for speech based emotion recognition. In particular, the use of phoneme sequences to encode verbal cues related to the expression of emotions is proposed and lexical features based on these phoneme sequences are introduced for use in automatic emotion recognition systems where manual transcripts are not available. Secondly, a novel estimate of emotional salience of verbal cues, applicable to both phoneme sequences and words, is presented.

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Authors:
Kalani Wataraka Gamage, Vidhyasaharan Sethu, Eliathamby Ambikairajah
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3 August 2017 - 3:55am
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http://ieeexplore.ieee.org/document/7953274/

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[1] Kalani Wataraka Gamage, Vidhyasaharan Sethu, Eliathamby Ambikairajah, "SALIENCE BASED LEXICAL FEATURES FOR EMOTION RECOGNITION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1800. Accessed: Nov. 23, 2017.
@article{1800-17,
url = {http://sigport.org/1800},
author = {Kalani Wataraka Gamage; Vidhyasaharan Sethu; Eliathamby Ambikairajah },
publisher = {IEEE SigPort},
title = {SALIENCE BASED LEXICAL FEATURES FOR EMOTION RECOGNITION},
year = {2017} }
TY - EJOUR
T1 - SALIENCE BASED LEXICAL FEATURES FOR EMOTION RECOGNITION
AU - Kalani Wataraka Gamage; Vidhyasaharan Sethu; Eliathamby Ambikairajah
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1800
ER -
Kalani Wataraka Gamage, Vidhyasaharan Sethu, Eliathamby Ambikairajah. (2017). SALIENCE BASED LEXICAL FEATURES FOR EMOTION RECOGNITION. IEEE SigPort. http://sigport.org/1800
Kalani Wataraka Gamage, Vidhyasaharan Sethu, Eliathamby Ambikairajah, 2017. SALIENCE BASED LEXICAL FEATURES FOR EMOTION RECOGNITION. Available at: http://sigport.org/1800.
Kalani Wataraka Gamage, Vidhyasaharan Sethu, Eliathamby Ambikairajah. (2017). "SALIENCE BASED LEXICAL FEATURES FOR EMOTION RECOGNITION." Web.
1. Kalani Wataraka Gamage, Vidhyasaharan Sethu, Eliathamby Ambikairajah. SALIENCE BASED LEXICAL FEATURES FOR EMOTION RECOGNITION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1800

Hand Gesture Recognition Using Ultrasonic Waves

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Authors:
Mohammed H. AlSharif, Mohamed Saad, Tareq Y. Al-Naffouri
Submitted On:
17 March 2017 - 7:18am
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ICASSP_2017_Poster.pdf

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[1] Mohammed H. AlSharif, Mohamed Saad, Tareq Y. Al-Naffouri , "Hand Gesture Recognition Using Ultrasonic Waves", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1774. Accessed: Nov. 23, 2017.
@article{1774-17,
url = {http://sigport.org/1774},
author = {Mohammed H. AlSharif; Mohamed Saad; Tareq Y. Al-Naffouri },
publisher = {IEEE SigPort},
title = {Hand Gesture Recognition Using Ultrasonic Waves},
year = {2017} }
TY - EJOUR
T1 - Hand Gesture Recognition Using Ultrasonic Waves
AU - Mohammed H. AlSharif; Mohamed Saad; Tareq Y. Al-Naffouri
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1774
ER -
Mohammed H. AlSharif, Mohamed Saad, Tareq Y. Al-Naffouri . (2017). Hand Gesture Recognition Using Ultrasonic Waves. IEEE SigPort. http://sigport.org/1774
Mohammed H. AlSharif, Mohamed Saad, Tareq Y. Al-Naffouri , 2017. Hand Gesture Recognition Using Ultrasonic Waves. Available at: http://sigport.org/1774.
Mohammed H. AlSharif, Mohamed Saad, Tareq Y. Al-Naffouri . (2017). "Hand Gesture Recognition Using Ultrasonic Waves." Web.
1. Mohammed H. AlSharif, Mohamed Saad, Tareq Y. Al-Naffouri . Hand Gesture Recognition Using Ultrasonic Waves [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1774

SIGNAL PROCESSING CUP 2017 - REAL-TIME BEAT TRACKING CHALLENGE - Results

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27 March 2017 - 9:38pm
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2017 SP CUP Results.pdf

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[1] , "SIGNAL PROCESSING CUP 2017 - REAL-TIME BEAT TRACKING CHALLENGE - Results", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1741. Accessed: Nov. 23, 2017.
@article{1741-17,
url = {http://sigport.org/1741},
author = { },
publisher = {IEEE SigPort},
title = {SIGNAL PROCESSING CUP 2017 - REAL-TIME BEAT TRACKING CHALLENGE - Results},
year = {2017} }
TY - EJOUR
T1 - SIGNAL PROCESSING CUP 2017 - REAL-TIME BEAT TRACKING CHALLENGE - Results
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1741
ER -
. (2017). SIGNAL PROCESSING CUP 2017 - REAL-TIME BEAT TRACKING CHALLENGE - Results. IEEE SigPort. http://sigport.org/1741
, 2017. SIGNAL PROCESSING CUP 2017 - REAL-TIME BEAT TRACKING CHALLENGE - Results. Available at: http://sigport.org/1741.
. (2017). "SIGNAL PROCESSING CUP 2017 - REAL-TIME BEAT TRACKING CHALLENGE - Results." Web.
1. . SIGNAL PROCESSING CUP 2017 - REAL-TIME BEAT TRACKING CHALLENGE - Results [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1741

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