Qiang Huang | DeepAI

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∙ 02/21/2023

Lightweight-Yet-Efficient: Revitalizing Ball-Tree for Point-to-Hyperplane Nearest Neighbor Search

Finding the nearest neighbor to a hyperplane (or Point-to-Hyperplane Nea...

0 Qiang Huang, et al. ∙

∙ 02/03/2023

Simple, Effective and General: A New Backbone for Cross-view Image Geo-localization

In this work, we aim at an important but less explored problem of a simp...

0 Yingying Zhu, et al. ∙

∙ 01/15/2023

Improving Reliability of Fine-tuning with Block-wise Optimisation

Finetuning can be used to tackle domain-specific tasks by transferring k...

0 Basel Barakat, et al. ∙

∙ 11/23/2022

SAH: Shifting-aware Asymmetric Hashing for Reverse k-Maximum Inner Product Search

This paper investigates a new yet challenging problem called Reverse k-M...

0 Qiang Huang, et al. ∙

∙ 02/22/2022

DIOT: Detecting Implicit Obstacles from Trajectories

In this paper, we study a new data mining problem of obstacle detection ...

0 Yifan Lei, et al. ∙

∙ 09/21/2021

Unsupervised Abstract Reasoning for Raven's Problem Matrices

Raven's Progressive Matrices (RPM) is highly correlated with human intel...

0 Tao Zhuo, et al. ∙

∙ 06/19/2021

A Generic Distributed Clustering Framework for Massive Data

In this paper, we introduce a novel Generic distributEd clustEring frame...

0 Pingyi Luo, et al. ∙

∙ 10/29/2020

T-vectors: Weakly Supervised Speaker Identification Using Hierarchical Transformer Model

Identifying multiple speakers without knowing where a speaker's voice is...

0 Yanpei Shi, et al. ∙

∙ 10/21/2020

Improving Audio Anomalies Recognition Using Temporal Convolutional Attention Network

Anomalous audio in speech recordings is often caused by speaker voice di...

0 Qiang Huang, et al. ∙

∙ 05/16/2020

Exploration of Audio Quality Assessment and Anomaly Localisation Using Attention Models

Many applications of speech technology require more and more audio data....

0 Qiang Huang, et al. ∙

∙ 05/15/2020

Speaker Re-identification with Speaker Dependent Speech Enhancement

While the use of deep neural networks has significantly boosted speaker ...

0 Yanpei Shi, et al. ∙

∙ 05/15/2020

Weakly Supervised Training of Hierarchical Attention Networks for Speaker Identification

Identifying multiple speakers without knowing where a speaker's voice is...

0 Yanpei Shi, et al. ∙

∙ 04/11/2020

Locality-Sensitive Hashing Scheme based on Longest Circular Co-Substring

Locality-Sensitive Hashing (LSH) is one of the most popular methods for ...

0 Yifan Lei, et al. ∙

∙ 01/17/2020

GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks

Graph structured data has wide applicability in various domains such as ...

22 Qiang Huang, et al. ∙

∙ 01/14/2020

Robust Speaker Recognition Using Speech Enhancement And Attention Model

In this paper, a novel architecture for speaker recognition is proposed ...

0 Yanpei Shi, et al. ∙

∙ 11/18/2019

Multi-task Sentence Encoding Model for Semantic Retrieval in Question Answering Systems

Question Answering (QA) systems are used to provide proper responses to ...

0 Qiang Huang, et al. ∙

∙ 10/17/2019

H-VECTORS: Utterance-level Speaker Embedding Using A Hierarchical Attention Model

In this paper, a hierarchical attention network to generate utterance-le...

0 Yanpei Shi, et al. ∙

∙ 10/16/2019

Contextual Joint Factor Acoustic Embeddings

Embedding acoustic information into fixed length representations is of i...

0 Yanpei Shi, et al. ∙

∙ 09/24/2019

Improving Robustness In Speaker Identification Using A Two-Stage Attention Model

In this paper a novel framework to tackle speaker recognition using a tw...

0 Yanpei Shi, et al. ∙

∙ 02/24/2017

Convolutional Gated Recurrent Neural Network Incorporating Spatial Features for Audio Tagging

Environmental audio tagging is a newly proposed task to predict the pres...

0 Yong Xu, et al. ∙

∙ 07/13/2016

Hierarchical learning for DNN-based acoustic scene classification

In this paper, we present a deep neural network (DNN)-based acoustic sce...

0 Yong Xu, et al. ∙

∙ 07/13/2016

Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging

Environmental audio tagging aims to predict only the presence or absence...

0 Yong Xu, et al. ∙

∙ 06/24/2016

Fully DNN-based Multi-label regression for audio tagging

Acoustic event detection for content analysis in most cases relies on lo...

0 Yong Xu, et al. ∙