ICASSP 2021 - IEEE International Conference on Acoustics, Speech and Signal Processing is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The ICASSP 2021 conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world. Visit website.
- Read more about AGGREGATION ARCHITECTURE AND ALL-TO-ONE NETWORK FOR REAL-TIME SEMANTIC SEGMENTATION
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Poster%231683.pdf
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- Read more about Optimum Feature Ordering for Dynamic Instance–wise Joint Feature Selection and Classification
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poster.pdf
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- Read more about Instance segmentation with the number of clusters incorporated in embedding learning
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Poster.pdf
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- Read more about ICASSP 2021 Poster - SPARSE RECOVERY BEAMFORMING AND UPSCALING IN THE RAY SPACE
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We have been exploring the integration of sparse recovery methods into the ray space transform over the past years and now demonstrate the potential and benefits of beamforming and upscaling signals in the integrated ray space and sparse recovery domain. A primary advantage of the ray space approach derives from its robust ability to integrate information from multiple arrays and viewpoints. Nonetheless, for a given viewpoint, the ray space technique requires a dense array that can be divided into sub-arrays enabling the plenacoustic approach to signal processing.
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- Read more about ADAPTIVE RE-BALANCING NETWORK WITH GATE MECHANISM FOR LONG-TAILED VISUAL QUESTION ANSWERING
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- Read more about On Permutation Invariant Training for Speech Source Separation
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poster.pdf
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In this paper, we present a novel Image Fusion Model
(IFM) for ECG heart-beat classification to overcome the
weaknesses of existing machine learning techniques that rely
either on manual feature extraction or direct utilization of 1D
raw ECG signal. At the input of IFM, we first convert the
heart-beats of ECG into three different images using Gramian
Angular Field (GAF), Recurrence Plot (RP) and Markov
Transition Field (MTF) and then fuse these images to create
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- Read more about Relying on a rate constraint to reduce Motion Estimation complexity
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Slides and poster presented during ICASSP 2021 about our work on "Relying on a rate constraint to reduce Motion Estimation complexity".
slides.pdf
poster.pdf
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