ICASSP is the world's largest and most comprehensive technical conference on signal processing and its applications. It provides a fantastic networking opportunity for like-minded professionals from around the world. ICASSP 2016 conference will feature world-class presentations by internationally renowned speakers and cutting-edge session topics.
- Read more about A New Approach for Heart Rate Monitoring using Photoplethysmography Signals Contaminated by MotionArtifacts
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We considered the problem of accurately estimating the heart rate (HR) using photoplethysmography (PPG) signals that are contaminated by motion artifacts (MA). A novel HR estimation approach based on GRidless spectral Estimation and SVM-based peak Selection, denoted by GRESS, was proposed. It first obtained the sparse spectrum of PPG using a continuous dictionary, then a simple spectral subtraction step was adopted to remove MA, finally an SVM-based method was developed to select the spectral peak corresponding to HR.
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- Read more about Memory Reduction Techniques for Successive Cancellation Decoding of Polar Codes
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Polar coding is a new coding scheme that asymptotically achieves the capacity of several communication channels. Polar codes can be decoded with a successive cancellation (SC) decoder. In terms of hardware implementation, archi- tectural performance of SC decoders is limited by the memory complexity. In this paper, two complementary methods are proposed to reduce the memory footprint of current state-of- the-art SC decoders. These methods must also applicable to SC-List decoders.
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- Read more about QUANTIFICATION OF BALANCE IN SINGLE LIMB STANCE USING KINECT
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Poster for the work titled - "QUANTIFICATION OF BALANCE IN SINGLE LIMB STANCE USING KINECT".
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- Read more about ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION
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- Read more about MULTI-VIEW DISTRIBUTED SOURCE CODING OF BINARY FEATURES FOR VISUAL SENSOR NETWORKS
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This is an overview poster on recent research of visual analysis algorithms in visual sensor networks. With the following abstract:
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- Read more about Target detection for depth imaging using sparse single-photon data
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This paper presents a new Bayesian model and associated algorithm
for depth and intensity profiling using full waveforms from timecorrelated
single-photon counting (TCSPC) measurements when the
photon count in very low. The model represents each Lidar waveform
as an unknown constant background level, which is combined
in the presence of a target, to a known impulse response weighted
by the target intensity and finally corrupted by Poisson noise. The
joint target detection and depth imaging problem is expressed as a
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- Read more about Face Alignment by Deep Convolutional Network with Adaptive Learning Rate
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Deep convolutional network has been widely used in face recognition while not often used in face alignment. One of the most important reasons of this is the lack of training images annotated with landmarks due to fussy and time-consuming annotation work. To overcome this problem, we propose a novel data augmentation strategy. And we design an innovative training algorithm with adaptive learning rate for two iterative procedures, which helps the network to search an optimal solution.
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- Read more about Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement
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ICASSP2016.pdf
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![Binary image reconstruction: proposed method vs basis pursuit Binary image reconstruction: proposed method vs basis pursuit](https://sigport.org/sites/default/files/styles/list/public/Media%20Root/presentation_icassp2016.001_0.jpeg?itok=Zuwo-F42)
This is the IEEE SPL presentation of the author's paper:
M. Nagahara, "Discrete Signal Reconstruction by Sum of Absolute Values," in IEEE Signal Processing Letters, vol. 22, no. 10, pp. 1575-1579, Oct. 2015.
doi: 10.1109/LSP.2015.2414932
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7064695&isnumber...
icassp2016.pdf
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- Read more about Sparse Phase Retrieval with Near Minimal Measurements: A Structured Sampling Based Approach
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