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Found 10 papers, 2 papers with code
WCCNet: Wavelet-integrated CNN with Crossmodal Rearranging Fusion for Fast Multispectral Pedestrian Detection
Multispectral pedestrian detection achieves better visibility in challenging conditions and thus has a broad application in various tasks, for which both the accuracy and computational cost are of paramount importance.
Optimization of Directional Landmark Deployment for Visual Observer on SE(3)
An optimization method is proposed in this paper for novel deployment of given number of directional landmarks (location and pose) within a given region in the 3-D task space.
Coverage Optimization of Camera Network for Continuous Deformable Object
To reduce the computational complexity, some feature points are carefully selected representing the continuous deformation process, and the visual coverage for the deformable object is transferred to cover the specific feature points.
Transferring Dual Stochastic Graph Convolutional Network for Facial Micro-expression Recognition
To improve the recognition performance of the small micro-expression data, this paper presents a transferring dual stochastic Graph Convolutional Network (TDSGCN) model.
Optimal Memory Scheme for Accelerated Consensus Over Multi-Agent Networks
The contributions of this paper are three: (i) For the one-tap memory scheme, we demonstrate that the state deviation memory is useless for the optimal convergence.
Distributed Frequency Restoration and SoC Balancing Control for AC Microgrids
This paper develops an improved distributed finite-time control algorithm for multiagent-based ac microgrids with battery energy storage systems (BESSs) utilizing a low-width communication network.
PET Image Reconstruction with Multiple Kernels and Multiple Kernel Space Regularizers
To reduce the reconstruction error and the sensitivity to iteration number, we present a general class of multi-kernel matrices and two regularizers consisting of kernel image dictionary and kernel image Laplacian quatradic, and use them to derive the single-kernel regularized EM and multi-kernel regularized EM algorithms for PET image reconstruction.
A Two-Stage Approach to Device-Robust Acoustic Scene Classification
To improve device robustness, a highly desirable key feature of a competitive data-driven acoustic scene classification (ASC) system, a novel two-stage system based on fully convolutional neural networks (CNNs) is proposed.
Ranked #1 on
Acoustic Scene Classification
on TAU Urban Acoustic Scenes 2019
(using extra training data)
A Noise-Aware Memory-Attention Network Architecture for Regression-Based Speech Enhancement
We propose a novel noise-aware memory-attention network (NAMAN) for regression-based speech enhancement, aiming at improving quality of enhanced speech in unseen noise conditions.
Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation
On Task 1b development data set, we achieve an accuracy of 96. 7\% with a model size smaller than 500KB.
