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Audio and Acoustic Signal Processing

A Supervised Air-Tissue Boundary Segmentation Technique in real-time Magnetic Resonance Imaging Video using a Novel Measure of Contrast and Dynamic Programming

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Authors:
Prasanta Kumar Ghosh
Submitted On:
14 April 2018 - 12:13am
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ICASSP_presentation_Advait_apr_14.pdf

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[1] Prasanta Kumar Ghosh, "A Supervised Air-Tissue Boundary Segmentation Technique in real-time Magnetic Resonance Imaging Video using a Novel Measure of Contrast and Dynamic Programming", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2792. Accessed: Sep. 24, 2018.
@article{2792-18,
url = {http://sigport.org/2792},
author = {Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = {A Supervised Air-Tissue Boundary Segmentation Technique in real-time Magnetic Resonance Imaging Video using a Novel Measure of Contrast and Dynamic Programming},
year = {2018} }
TY - EJOUR
T1 - A Supervised Air-Tissue Boundary Segmentation Technique in real-time Magnetic Resonance Imaging Video using a Novel Measure of Contrast and Dynamic Programming
AU - Prasanta Kumar Ghosh
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2792
ER -
Prasanta Kumar Ghosh. (2018). A Supervised Air-Tissue Boundary Segmentation Technique in real-time Magnetic Resonance Imaging Video using a Novel Measure of Contrast and Dynamic Programming. IEEE SigPort. http://sigport.org/2792
Prasanta Kumar Ghosh, 2018. A Supervised Air-Tissue Boundary Segmentation Technique in real-time Magnetic Resonance Imaging Video using a Novel Measure of Contrast and Dynamic Programming. Available at: http://sigport.org/2792.
Prasanta Kumar Ghosh. (2018). "A Supervised Air-Tissue Boundary Segmentation Technique in real-time Magnetic Resonance Imaging Video using a Novel Measure of Contrast and Dynamic Programming." Web.
1. Prasanta Kumar Ghosh. A Supervised Air-Tissue Boundary Segmentation Technique in real-time Magnetic Resonance Imaging Video using a Novel Measure of Contrast and Dynamic Programming [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2792

Crowdsourcing Emotional Speech


We describe the methodology for the collection and annotation of a large corpus of emotional speech data through crowdsourcing. The corpus offers 187 hours of data from 2,965 subjects. Data includes non-emotional recordings from each subject as well as recordings for five emotions: angry, happy-low-arousal, happy-high-arousal, neutral,

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Authors:
Jennifer Smith, Andreas Tsiartas, Valerie Wagner, Elizabeth Shriberg, Nikoletta Bassiou
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13 April 2018 - 10:55pm
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ICASSP_SenSay_Poster_180409.pdf

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[1] Jennifer Smith, Andreas Tsiartas, Valerie Wagner, Elizabeth Shriberg, Nikoletta Bassiou, "Crowdsourcing Emotional Speech", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2786. Accessed: Sep. 24, 2018.
@article{2786-18,
url = {http://sigport.org/2786},
author = {Jennifer Smith; Andreas Tsiartas; Valerie Wagner; Elizabeth Shriberg; Nikoletta Bassiou },
publisher = {IEEE SigPort},
title = {Crowdsourcing Emotional Speech},
year = {2018} }
TY - EJOUR
T1 - Crowdsourcing Emotional Speech
AU - Jennifer Smith; Andreas Tsiartas; Valerie Wagner; Elizabeth Shriberg; Nikoletta Bassiou
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2786
ER -
Jennifer Smith, Andreas Tsiartas, Valerie Wagner, Elizabeth Shriberg, Nikoletta Bassiou. (2018). Crowdsourcing Emotional Speech. IEEE SigPort. http://sigport.org/2786
Jennifer Smith, Andreas Tsiartas, Valerie Wagner, Elizabeth Shriberg, Nikoletta Bassiou, 2018. Crowdsourcing Emotional Speech. Available at: http://sigport.org/2786.
Jennifer Smith, Andreas Tsiartas, Valerie Wagner, Elizabeth Shriberg, Nikoletta Bassiou. (2018). "Crowdsourcing Emotional Speech." Web.
1. Jennifer Smith, Andreas Tsiartas, Valerie Wagner, Elizabeth Shriberg, Nikoletta Bassiou. Crowdsourcing Emotional Speech [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2786

TOWARDS PREDICTING PHYSIOLOGY FROM SPEECH DURING STRESSFUL CONVERSATIONS: HEART RATE AND RESPIRATORY SINUS ARRHYTHMIA


Being affected by mental stress during conversations might have a direct or indirect effect on our speech acoustics as well as on our physiological responses. This paper presents a study on finding the relationship between these two modalities, speech acoustics and physiology, during stressful conversations between humans. Heart rate and respiratory sinus arrhythmia have been considered as physiological variables in the present study. Two datasets, one from stress induction sessions and the other one from in-lab discussions of relationship conflicts between couples, have been analyzed.

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Authors:
Arindam Jati, Paula Williams, Brian Baucom, Panayiotis Georgiou
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16 April 2018 - 11:15pm
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Stress_JatiWilliamsBaucomGeorgiou_final.pptx

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Stress_JatiWilliamsBaucomGeorgiou_final_AJEdits.pptx

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[1] Arindam Jati, Paula Williams, Brian Baucom, Panayiotis Georgiou, "TOWARDS PREDICTING PHYSIOLOGY FROM SPEECH DURING STRESSFUL CONVERSATIONS: HEART RATE AND RESPIRATORY SINUS ARRHYTHMIA", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2775. Accessed: Sep. 24, 2018.
@article{2775-18,
url = {http://sigport.org/2775},
author = {Arindam Jati; Paula Williams; Brian Baucom; Panayiotis Georgiou },
publisher = {IEEE SigPort},
title = {TOWARDS PREDICTING PHYSIOLOGY FROM SPEECH DURING STRESSFUL CONVERSATIONS: HEART RATE AND RESPIRATORY SINUS ARRHYTHMIA},
year = {2018} }
TY - EJOUR
T1 - TOWARDS PREDICTING PHYSIOLOGY FROM SPEECH DURING STRESSFUL CONVERSATIONS: HEART RATE AND RESPIRATORY SINUS ARRHYTHMIA
AU - Arindam Jati; Paula Williams; Brian Baucom; Panayiotis Georgiou
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2775
ER -
Arindam Jati, Paula Williams, Brian Baucom, Panayiotis Georgiou. (2018). TOWARDS PREDICTING PHYSIOLOGY FROM SPEECH DURING STRESSFUL CONVERSATIONS: HEART RATE AND RESPIRATORY SINUS ARRHYTHMIA. IEEE SigPort. http://sigport.org/2775
Arindam Jati, Paula Williams, Brian Baucom, Panayiotis Georgiou, 2018. TOWARDS PREDICTING PHYSIOLOGY FROM SPEECH DURING STRESSFUL CONVERSATIONS: HEART RATE AND RESPIRATORY SINUS ARRHYTHMIA. Available at: http://sigport.org/2775.
Arindam Jati, Paula Williams, Brian Baucom, Panayiotis Georgiou. (2018). "TOWARDS PREDICTING PHYSIOLOGY FROM SPEECH DURING STRESSFUL CONVERSATIONS: HEART RATE AND RESPIRATORY SINUS ARRHYTHMIA." Web.
1. Arindam Jati, Paula Williams, Brian Baucom, Panayiotis Georgiou. TOWARDS PREDICTING PHYSIOLOGY FROM SPEECH DURING STRESSFUL CONVERSATIONS: HEART RATE AND RESPIRATORY SINUS ARRHYTHMIA [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2775

QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION


In this presentation, the effects of quantisation on distributed convex optimisation algorithms are explored via the lens of monotone operator theory. Specifically, by representing transmission quantisation via an additive noise model, we demonstrate how quantisation can be viewed as an instance of an inexact Krasnoselskii-Mann scheme. In the case of two distributed solvers, the Alternating Direction Method of Multipliers and the Primal Dual Method of Multipliers, we further demonstrate how an adaptive quantisation scheme can be constructed to reduce transmission costs between nodes.

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Authors:
Richard Heusdens
Submitted On:
13 April 2018 - 4:27pm
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Presentation QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION.pdf

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[1] Richard Heusdens, "QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2764. Accessed: Sep. 24, 2018.
@article{2764-18,
url = {http://sigport.org/2764},
author = {Richard Heusdens },
publisher = {IEEE SigPort},
title = {QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION},
year = {2018} }
TY - EJOUR
T1 - QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION
AU - Richard Heusdens
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2764
ER -
Richard Heusdens. (2018). QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION. IEEE SigPort. http://sigport.org/2764
Richard Heusdens, 2018. QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION. Available at: http://sigport.org/2764.
Richard Heusdens. (2018). "QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION." Web.
1. Richard Heusdens. QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2764

MULTI-VIEW AUDIO-ARTICULATORY FEATURES FOR PHONETIC RECOGNITION ON RTMRI-TIMIT DATABASE


In this paper, we investigate the use of articulatory informa-
tion, and more specifically real time Magnetic Resonance
Imaging (rtMRI) data of the vocal tract, to improve speech
recognition performance. For the purpose of our experiments,
we use data from the rtMRI-TIMIT database. Firstly, Scale
Invariant Feature Transform (SIFT) features are extracted for
each video frame. Afterwards, the SIFT descriptors of each
frame are transformed to a single histogram per picture, by
using the Bag of Visual Words methodology. Since this kind

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Authors:
Ioannis Douros, Athanasios Katsamanis, Petros Maragos
Submitted On:
13 April 2018 - 2:13pm
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ICASSP_2018_poster_final.pdf

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[1] Ioannis Douros, Athanasios Katsamanis, Petros Maragos, "MULTI-VIEW AUDIO-ARTICULATORY FEATURES FOR PHONETIC RECOGNITION ON RTMRI-TIMIT DATABASE", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2734. Accessed: Sep. 24, 2018.
@article{2734-18,
url = {http://sigport.org/2734},
author = {Ioannis Douros; Athanasios Katsamanis; Petros Maragos },
publisher = {IEEE SigPort},
title = {MULTI-VIEW AUDIO-ARTICULATORY FEATURES FOR PHONETIC RECOGNITION ON RTMRI-TIMIT DATABASE},
year = {2018} }
TY - EJOUR
T1 - MULTI-VIEW AUDIO-ARTICULATORY FEATURES FOR PHONETIC RECOGNITION ON RTMRI-TIMIT DATABASE
AU - Ioannis Douros; Athanasios Katsamanis; Petros Maragos
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2734
ER -
Ioannis Douros, Athanasios Katsamanis, Petros Maragos. (2018). MULTI-VIEW AUDIO-ARTICULATORY FEATURES FOR PHONETIC RECOGNITION ON RTMRI-TIMIT DATABASE. IEEE SigPort. http://sigport.org/2734
Ioannis Douros, Athanasios Katsamanis, Petros Maragos, 2018. MULTI-VIEW AUDIO-ARTICULATORY FEATURES FOR PHONETIC RECOGNITION ON RTMRI-TIMIT DATABASE. Available at: http://sigport.org/2734.
Ioannis Douros, Athanasios Katsamanis, Petros Maragos. (2018). "MULTI-VIEW AUDIO-ARTICULATORY FEATURES FOR PHONETIC RECOGNITION ON RTMRI-TIMIT DATABASE." Web.
1. Ioannis Douros, Athanasios Katsamanis, Petros Maragos. MULTI-VIEW AUDIO-ARTICULATORY FEATURES FOR PHONETIC RECOGNITION ON RTMRI-TIMIT DATABASE [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2734

A CONVERSATIONAL NEURAL LANGUAGE MODEL FOR SPEECH RECOGNITION IN DIGITAL ASSISTANTS


Speech recognition in digital assistants such as Google Assistant can
potentially benefit from the use of conversational context consisting of user
queries and responses from the agent. We explore the use of recurrent,
Long Short-Term Memory (LSTM), neural language models (LMs) to model the conversations
in a digital assistant. Our proposed methods effectively capture the context of
previous utterances in a conversation without modifying the underlying LSTM
architecture. We demonstrate a 4% relative improvement in recognition performance

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Authors:
Eunjoon Cho, Shankar Kumar
Submitted On:
13 April 2018 - 1:19pm
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conversation.pdf

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[1] Eunjoon Cho, Shankar Kumar, "A CONVERSATIONAL NEURAL LANGUAGE MODEL FOR SPEECH RECOGNITION IN DIGITAL ASSISTANTS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2732. Accessed: Sep. 24, 2018.
@article{2732-18,
url = {http://sigport.org/2732},
author = {Eunjoon Cho; Shankar Kumar },
publisher = {IEEE SigPort},
title = {A CONVERSATIONAL NEURAL LANGUAGE MODEL FOR SPEECH RECOGNITION IN DIGITAL ASSISTANTS},
year = {2018} }
TY - EJOUR
T1 - A CONVERSATIONAL NEURAL LANGUAGE MODEL FOR SPEECH RECOGNITION IN DIGITAL ASSISTANTS
AU - Eunjoon Cho; Shankar Kumar
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2732
ER -
Eunjoon Cho, Shankar Kumar. (2018). A CONVERSATIONAL NEURAL LANGUAGE MODEL FOR SPEECH RECOGNITION IN DIGITAL ASSISTANTS. IEEE SigPort. http://sigport.org/2732
Eunjoon Cho, Shankar Kumar, 2018. A CONVERSATIONAL NEURAL LANGUAGE MODEL FOR SPEECH RECOGNITION IN DIGITAL ASSISTANTS. Available at: http://sigport.org/2732.
Eunjoon Cho, Shankar Kumar. (2018). "A CONVERSATIONAL NEURAL LANGUAGE MODEL FOR SPEECH RECOGNITION IN DIGITAL ASSISTANTS." Web.
1. Eunjoon Cho, Shankar Kumar. A CONVERSATIONAL NEURAL LANGUAGE MODEL FOR SPEECH RECOGNITION IN DIGITAL ASSISTANTS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2732

USING ACCELEROMETRIC AND GYROSCOPIC DATA TO IMPROVE BLOOD PRESSURE PREDICTION FROM PULSE TRANSIT TIME USING RECURRENT NEURAL NETWORK

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Authors:
Shrimanti Ghosh, Ankur Banerjee, Nilanjan Ray, Peter W Wood, Pierre Boulanger, Raj Padwal
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13 April 2018 - 12:27pm
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ICASSP_2018_Poster.pdf

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[1] Shrimanti Ghosh, Ankur Banerjee, Nilanjan Ray, Peter W Wood, Pierre Boulanger, Raj Padwal, "USING ACCELEROMETRIC AND GYROSCOPIC DATA TO IMPROVE BLOOD PRESSURE PREDICTION FROM PULSE TRANSIT TIME USING RECURRENT NEURAL NETWORK", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2727. Accessed: Sep. 24, 2018.
@article{2727-18,
url = {http://sigport.org/2727},
author = {Shrimanti Ghosh; Ankur Banerjee; Nilanjan Ray; Peter W Wood; Pierre Boulanger; Raj Padwal },
publisher = {IEEE SigPort},
title = {USING ACCELEROMETRIC AND GYROSCOPIC DATA TO IMPROVE BLOOD PRESSURE PREDICTION FROM PULSE TRANSIT TIME USING RECURRENT NEURAL NETWORK},
year = {2018} }
TY - EJOUR
T1 - USING ACCELEROMETRIC AND GYROSCOPIC DATA TO IMPROVE BLOOD PRESSURE PREDICTION FROM PULSE TRANSIT TIME USING RECURRENT NEURAL NETWORK
AU - Shrimanti Ghosh; Ankur Banerjee; Nilanjan Ray; Peter W Wood; Pierre Boulanger; Raj Padwal
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2727
ER -
Shrimanti Ghosh, Ankur Banerjee, Nilanjan Ray, Peter W Wood, Pierre Boulanger, Raj Padwal. (2018). USING ACCELEROMETRIC AND GYROSCOPIC DATA TO IMPROVE BLOOD PRESSURE PREDICTION FROM PULSE TRANSIT TIME USING RECURRENT NEURAL NETWORK. IEEE SigPort. http://sigport.org/2727
Shrimanti Ghosh, Ankur Banerjee, Nilanjan Ray, Peter W Wood, Pierre Boulanger, Raj Padwal, 2018. USING ACCELEROMETRIC AND GYROSCOPIC DATA TO IMPROVE BLOOD PRESSURE PREDICTION FROM PULSE TRANSIT TIME USING RECURRENT NEURAL NETWORK. Available at: http://sigport.org/2727.
Shrimanti Ghosh, Ankur Banerjee, Nilanjan Ray, Peter W Wood, Pierre Boulanger, Raj Padwal. (2018). "USING ACCELEROMETRIC AND GYROSCOPIC DATA TO IMPROVE BLOOD PRESSURE PREDICTION FROM PULSE TRANSIT TIME USING RECURRENT NEURAL NETWORK." Web.
1. Shrimanti Ghosh, Ankur Banerjee, Nilanjan Ray, Peter W Wood, Pierre Boulanger, Raj Padwal. USING ACCELEROMETRIC AND GYROSCOPIC DATA TO IMPROVE BLOOD PRESSURE PREDICTION FROM PULSE TRANSIT TIME USING RECURRENT NEURAL NETWORK [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2727

Grid-Free Direction-of-Arrival Estimation with Compressed Sensing and Arbitrary Antenna Arrays


We study the problem of direction of arrival estimation for arbitrary antenna
arrays. We formulate it as a continuous line spectral estimation problem and solve it under
a sparsity prior without any gridding assumptions. Moreover, we incorporate the
array's beampattern in form of the Effective Aperture Distribution Function
(EADF), which allows to use arbitrary (synthetic as well as measured) antenna
arrays. This generalizes known atomic norm based grid-free DOA estimation methods (that

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Authors:
Florian Roemer, Thomas Hotz, Giovanni Del Galdo
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13 April 2018 - 9:54am
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[1] Florian Roemer, Thomas Hotz, Giovanni Del Galdo, "Grid-Free Direction-of-Arrival Estimation with Compressed Sensing and Arbitrary Antenna Arrays", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2705. Accessed: Sep. 24, 2018.
@article{2705-18,
url = {http://sigport.org/2705},
author = {Florian Roemer; Thomas Hotz; Giovanni Del Galdo },
publisher = {IEEE SigPort},
title = {Grid-Free Direction-of-Arrival Estimation with Compressed Sensing and Arbitrary Antenna Arrays},
year = {2018} }
TY - EJOUR
T1 - Grid-Free Direction-of-Arrival Estimation with Compressed Sensing and Arbitrary Antenna Arrays
AU - Florian Roemer; Thomas Hotz; Giovanni Del Galdo
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2705
ER -
Florian Roemer, Thomas Hotz, Giovanni Del Galdo. (2018). Grid-Free Direction-of-Arrival Estimation with Compressed Sensing and Arbitrary Antenna Arrays. IEEE SigPort. http://sigport.org/2705
Florian Roemer, Thomas Hotz, Giovanni Del Galdo, 2018. Grid-Free Direction-of-Arrival Estimation with Compressed Sensing and Arbitrary Antenna Arrays. Available at: http://sigport.org/2705.
Florian Roemer, Thomas Hotz, Giovanni Del Galdo. (2018). "Grid-Free Direction-of-Arrival Estimation with Compressed Sensing and Arbitrary Antenna Arrays." Web.
1. Florian Roemer, Thomas Hotz, Giovanni Del Galdo. Grid-Free Direction-of-Arrival Estimation with Compressed Sensing and Arbitrary Antenna Arrays [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2705

REAL-TIME TOTAL FOCUSING METHOD FOR ULTRASONIC IMAGING OF MULTILAYERED OBJECT

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Authors:
Wenkai Cui, Kaihuai Qin
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13 April 2018 - 8:22am
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2265_lecture

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[1] Wenkai Cui, Kaihuai Qin, "REAL-TIME TOTAL FOCUSING METHOD FOR ULTRASONIC IMAGING OF MULTILAYERED OBJECT", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2697. Accessed: Sep. 24, 2018.
@article{2697-18,
url = {http://sigport.org/2697},
author = {Wenkai Cui; Kaihuai Qin },
publisher = {IEEE SigPort},
title = {REAL-TIME TOTAL FOCUSING METHOD FOR ULTRASONIC IMAGING OF MULTILAYERED OBJECT},
year = {2018} }
TY - EJOUR
T1 - REAL-TIME TOTAL FOCUSING METHOD FOR ULTRASONIC IMAGING OF MULTILAYERED OBJECT
AU - Wenkai Cui; Kaihuai Qin
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2697
ER -
Wenkai Cui, Kaihuai Qin. (2018). REAL-TIME TOTAL FOCUSING METHOD FOR ULTRASONIC IMAGING OF MULTILAYERED OBJECT. IEEE SigPort. http://sigport.org/2697
Wenkai Cui, Kaihuai Qin, 2018. REAL-TIME TOTAL FOCUSING METHOD FOR ULTRASONIC IMAGING OF MULTILAYERED OBJECT. Available at: http://sigport.org/2697.
Wenkai Cui, Kaihuai Qin. (2018). "REAL-TIME TOTAL FOCUSING METHOD FOR ULTRASONIC IMAGING OF MULTILAYERED OBJECT." Web.
1. Wenkai Cui, Kaihuai Qin. REAL-TIME TOTAL FOCUSING METHOD FOR ULTRASONIC IMAGING OF MULTILAYERED OBJECT [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2697

REAL-TIME TOTAL FOCUSING METHOD IMAGING FOR ULTRASONIC INSPECTION OF THREE-DIMENSIONAL MULTILAYERED MEDIA

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Authors:
Wenkai Cui, Kaihuai Qin
Submitted On:
13 April 2018 - 8:16am
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1502_Poster

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[1] Wenkai Cui, Kaihuai Qin, "REAL-TIME TOTAL FOCUSING METHOD IMAGING FOR ULTRASONIC INSPECTION OF THREE-DIMENSIONAL MULTILAYERED MEDIA", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2695. Accessed: Sep. 24, 2018.
@article{2695-18,
url = {http://sigport.org/2695},
author = {Wenkai Cui; Kaihuai Qin },
publisher = {IEEE SigPort},
title = {REAL-TIME TOTAL FOCUSING METHOD IMAGING FOR ULTRASONIC INSPECTION OF THREE-DIMENSIONAL MULTILAYERED MEDIA},
year = {2018} }
TY - EJOUR
T1 - REAL-TIME TOTAL FOCUSING METHOD IMAGING FOR ULTRASONIC INSPECTION OF THREE-DIMENSIONAL MULTILAYERED MEDIA
AU - Wenkai Cui; Kaihuai Qin
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2695
ER -
Wenkai Cui, Kaihuai Qin. (2018). REAL-TIME TOTAL FOCUSING METHOD IMAGING FOR ULTRASONIC INSPECTION OF THREE-DIMENSIONAL MULTILAYERED MEDIA. IEEE SigPort. http://sigport.org/2695
Wenkai Cui, Kaihuai Qin, 2018. REAL-TIME TOTAL FOCUSING METHOD IMAGING FOR ULTRASONIC INSPECTION OF THREE-DIMENSIONAL MULTILAYERED MEDIA. Available at: http://sigport.org/2695.
Wenkai Cui, Kaihuai Qin. (2018). "REAL-TIME TOTAL FOCUSING METHOD IMAGING FOR ULTRASONIC INSPECTION OF THREE-DIMENSIONAL MULTILAYERED MEDIA." Web.
1. Wenkai Cui, Kaihuai Qin. REAL-TIME TOTAL FOCUSING METHOD IMAGING FOR ULTRASONIC INSPECTION OF THREE-DIMENSIONAL MULTILAYERED MEDIA [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2695

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