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07/25/2023
On-Device Speaker Anonymization of Acoustic Embeddings for ASR based onFlexible Location Gradient Reversal Layer
Smart devices serviced by large-scale AI models necessitates user data t...
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07/24/2023
Online Continual Learning in Keyword Spotting for Low-Resource Devices via Pooling High-Order Temporal Statistics
Keyword Spotting (KWS) models on embedded devices should adapt fast to n...
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07/24/2023
A Model for Every User and Budget: Label-Free and Personalized Mixed-Precision Quantization
Recent advancement in Automatic Speech Recognition (ASR) has produced la...
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07/19/2023
Online Continual Learning for Robust Indoor Object Recognition
Vision systems mounted on home robots need to interact with unseen class...
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07/11/2022
pMCT: Patched Multi-Condition Training for Robust Speech Recognition
We propose a novel Patched Multi-Condition Training (pMCT) method for ro...
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06/06/2022
FedNST: Federated Noisy Student Training for Automatic Speech Recognition
Federated Learning (FL) enables training state-of-the-art Automatic Spee...
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05/11/2022
Deep Depth Completion: A Survey
Depth completion aims at predicting dense pixel-wise depth from a sparse...
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03/12/2022
A Mixed Quantization Network for Computationally Efficient Mobile Inverse Tone Mapping
Recovering a high dynamic range (HDR) image from a single low dynamic ra...
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02/11/2022
Adversarial Attacks and Defense Methods for Power Quality Recognition
Vulnerability of various machine learning methods to adversarial example...
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09/13/2021
Task Guided Compositional Representation Learning for ZDA
Zero-shot domain adaptation (ZDA) methods aim to transfer knowledge abou...
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05/19/2021
Prototype Guided Federated Learning of Visual Feature Representations
Federated Learning (FL) is a framework which enables distributed model t...
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12/11/2020
A New Neural Network Architecture Invariant to the Action of Symmetry Subgroups
We propose a computationally efficient G-invariant neural network that a...
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12/07/2020
Learning from Experience for Rapid Generation of Local Car Maneuvers
Being able to rapidly respond to the changing scenes and traffic situati...
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02/18/2020
A Computationally Efficient Neural Network Invariant to the Action of Symmetry Subgroups
We introduce a method to design a computationally efficient G-invariant ...
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05/22/2019
Fine-grained Optimization of Deep Neural Networks
In recent studies, several asymptotic upper bounds on generalization err...
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05/14/2019
Improving Head Pose Estimation with a Combined Loss and Bounding Box Margin Adjustment
We address a problem of estimating pose of a person's head from its RGB ...
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03/23/2018
Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries
We revisit the problem of estimating depth of a scene from its single RG...
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03/01/2018
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search
Researchers have applied deep neural networks to image restoration tasks...
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01/24/2018
Deep Structured Energy-Based Image Inpainting
In this paper, we propose a structured image inpainting method employing...
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12/12/2017
A vision based system for underwater docking
Autonomous underwater vehicles (AUVs) have been deployed for underwater ...
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11/06/2017
HyperNetworks with statistical filtering for defending adversarial examples
Deep learning algorithms have been known to be vulnerable to adversarial...
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07/25/2017
Linear Discriminant Generative Adversarial Networks
We develop a novel method for training of GANs for unsupervised and clas...
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07/25/2017
Improving Robustness of Feature Representations to Image Deformations using Powered Convolution in CNNs
In this work, we address the problem of improvement of robustness of fea...
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06/14/2017
Information Potential Auto-Encoders
In this paper, we suggest a framework to make use of mutual information ...
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04/03/2017
Truncating Wide Networks using Binary Tree Architectures
Recent study shows that a wide deep network can obtain accuracy comparab...
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01/22/2017
Optimization on Product Submanifolds of Convolution Kernels
Recent advances in optimization methods used for training convolutional ...
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10/22/2016
Optimization on Submanifolds of Convolution Kernels in CNNs
Kernel normalization methods have been employed to improve robustness of...
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10/17/2016
Encoding the Local Connectivity Patterns of fMRI for Cognitive State Classification
In this work, we propose a novel framework to encode the local connectiv...
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07/12/2016
Hierarchical Multi-resolution Mesh Networks for Brain Decoding
We propose a new framework, called Hierarchical Multi-resolution Mesh Ne...
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03/03/2016
Modeling the Sequence of Brain Volumes by Local Mesh Models for Brain Decoding
We represent the sequence of fMRI (Functional Magnetic Resonance Imaging...
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11/30/2015
Design of Kernels in Convolutional Neural Networks for Image Classification
Despite the effectiveness of Convolutional Neural Networks (CNNs) for im...
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03/04/2015
A Hierarchical Approach for Joint Multi-view Object Pose Estimation and Categorization
We propose a joint object pose estimation and categorization approach wh...
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02/18/2015
Fusion of Image Segmentation Algorithms using Consensus Clustering
A new segmentation fusion method is proposed that ensembles the output o...
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02/17/2015
Semi-supervised Segmentation Fusion of Multi-spectral and Aerial Images
A Semi-supervised Segmentation Fusion algorithm is proposed using consen...
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01/21/2015
A Graph Theoretic Approach for Object Shape Representation in Compositional Hierarchies Using a Hybrid Generative-Descriptive Model
A graph theoretic approach is proposed for object shape representation i...
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02/23/2014
Discriminative Functional Connectivity Measures for Brain Decoding
We propose a statistical learning model for classifying cognitive proces...
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05/10/2012