Search Results for author: Bin Yang

Found 110 papers, 28 papers with code

RetroGraph: Retrosynthetic Planning with Graph Search

1 code implementation23 Jun 2022 Shufang Xie, Rui Yan, Peng Han, Yingce Xia, Lijun Wu, Chenjuan Guo, Bin Yang, Tao Qin

We observe that the same intermediate molecules are visited many times in the searching process, and they are usually independently treated in previous tree-based methods (e. g., AND-OR tree search, Monte Carlo tree search).

Drug Discovery

Federated Latent Class Regression for Hierarchical Data

no code implementations22 Jun 2022 Bin Yang, Thomas Carette, Masanobu Jimbo, Shinya Maruyama

Federated Learning (FL) allows a number of agents to participate in training a global machine learning model without disclosing locally stored data.

Federated Learning

Conditional Seq2Seq model for the time-dependent two-level system

no code implementations6 Jun 2022 Bin Yang, Mengxi Wu, Winfried Teizer

We apply the deep learning neural network architecture to the two-level system in quantum optics to solve the time-dependent Schrodinger equation.

$(O,G)$-granular variable precision fuzzy rough sets based on overlap and grouping functions

no code implementations18 May 2022 Wei Li, Bin Yang, Junsheng Qiao

In this paper, the depiction of $(O, G)$-granular variable precision fuzzy rough sets ($(O, G)$-GVPFRSs for short) is first given based on overlap and grouping functions.

On three types of $L$-fuzzy $β$-covering-based rough sets

no code implementations13 May 2022 Wei Li, Bin Yang, Junsheng Qiao

In this paper, we mainly construct three types of $L$-fuzzy $\beta$-covering-based rough set models and study the axiom sets, matrix representations and interdependency of these three pairs of $L$-fuzzy $\beta$-covering-based rough approximation operators.

Some neighborhood-related fuzzy covering-based rough set models and their applications for decision making

no code implementations13 May 2022 Gongao Qi, Bin Yang, Wei Li

In order to further generalize the FRS theory to more complicated data environments, we firstly propose four types of fuzzy neighborhood operators based on fuzzy covering by overlap functions and their implicators in this paper.

Decision Making

Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection---Extended Version

no code implementations7 Apr 2022 Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen, Yan Zhao, Feiteng Huang, Kai Zheng

This is an extended version of "Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection", to appear in IEEE ICDE 2022.

Outlier Detection Time Series

Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning -- Extended Version

1 code implementation30 Mar 2022 Sean Bin Yang, Chenjuan Guo, Jilin Hu, Bin Yang, Jian Tang, Christian S. Jensen

In this setting, it is essential to learn generic temporal path representations(TPRs) that consider spatial and temporal correlations simultaneously and that can be used in different applications, i. e., downstream tasks.

Contrastive Learning Representation Learning

Towards Spatio-Temporal Aware Traffic Time Series Forecasting--Full Version

1 code implementation29 Mar 2022 Razvan-Gabriel Cirstea, Bin Yang, Chenjuan Guo, Tung Kieu, Shirui Pan

Such spatio-temporal agnostic models employ a shared parameter space irrespective of the time series locations and the time periods and they assume that the temporal patterns are similar across locations and do not evolve across time, which may not always hold, thus leading to sub-optimal results.

Time Series Time Series Forecasting

CMGAN: Conformer-based Metric GAN for Speech Enhancement

1 code implementation28 Mar 2022 Ruizhe Cao, Sherif Abdulatif, Bin Yang

The estimation of magnitude and complex spectrogram is decoupled in the decoder stage and then jointly incorporated to reconstruct the enhanced speech.

Automatic Speech Recognition Speech Enhancement

Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs

no code implementations17 Feb 2022 Ming Jin, Yu Zheng, Yuan-Fang Li, Siheng Chen, Bin Yang, Shirui Pan

Multivariate time series forecasting has long received significant attention in real-world applications, such as energy consumption and traffic prediction.

Multivariate Time Series Forecasting Time Series +1

GLPU: A Geometric Approach For Lidar Pointcloud Upsampling

no code implementations8 Feb 2022 George Eskandar, Janaranjani Palaniswamy, Karim Guirguis, Barath Somashekar, Bin Yang

Lidar sensors vary in vertical resolutions, where a denser pointcloud depicts a more detailed environment, albeit at a significantly higher cost.

Autonomous Driving

Fast solver for J2-perturbed Lambert problem using deep neural network

no code implementations9 Jan 2022 Bin Yang, Shuang Li, Jinglang Feng, Massimiliano Vasile

The intelligent initial guess generator is a deep neural network that is trained to correct the initial velocity vector coming from the solution of the unperturbed Lambert problem.

AutoCTS: Automated Correlated Time Series Forecasting -- Extended Version

no code implementations21 Dec 2021 Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, Christian S. Jensen

Specifically, we design both a micro and a macro search space to model possible architectures of ST-blocks and the connections among heterogeneous ST-blocks, and we provide a search strategy that is able to jointly explore the search spaces to identify optimal forecasting models.

Time Series Time Series Forecasting

BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule

no code implementations CVPR 2022 Miao Zhang, Jilin Hu, Steven Su, Shirui Pan, Xiaojun Chang, Bin Yang, Gholamreza Haffari

Differentiable Architecture Search (DARTS) has received massive attention in recent years, mainly because it significantly reduces the computational cost through weight sharing and continuous relaxation.

Neural Architecture Search Variational Inference

Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles -- Extended Version

no code implementations22 Nov 2021 David Campos, Tung Kieu, Chenjuan Guo, Feiteng Huang, Kai Zheng, Bin Yang, Christian S. Jensen

To improve accuracy, the ensemble employs multiple basic outlier detection models built on convolutional sequence-to-sequence autoencoders that can capture temporal dependencies in time series.

Outlier Detection Time Series

USIS: Unsupervised Semantic Image Synthesis

no code implementations29 Sep 2021 George Eskandar, Mohamed Abdelsamad, Karim Armanious, Bin Yang

Semantic Image Synthesis (SIS) is a subclass of image-to-image translation where a photorealistic image is synthesized from a segmentation mask.

Image-to-Image Translation Translation

Spatiotemporal Representation Learning on Time Series with Dynamic Graph ODEs

no code implementations29 Sep 2021 Ming Jin, Yuan-Fang Li, Yu Zheng, Bin Yang, Shirui Pan

Spatiotemporal representation learning on multivariate time series has received tremendous attention in forecasting traffic and energy data.

Graph structure learning Representation Learning +1

Improving Uncertainty of Deep Learning-based Object Classification on Radar Spectra using Label Smoothing

no code implementations27 Sep 2021 Kanil Patel, William Beluch, Kilian Rambach, Michael Pfeiffer, Bin Yang

The focus of this article is to learn deep radar spectra classifiers which offer robust real-time uncertainty estimates using label smoothing during training.

Decision Making

Differentiable Architecture Search Meets Network Pruning at Initialization: A More Reliable, Efficient, and Flexible Framework

no code implementations22 Jun 2021 Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Wei Huang, Bin Yang, Gholamreza Haffari

Although Differentiable ARchiTecture Search (DARTS) has become the mainstream paradigm in Neural Architecture Search (NAS) due to its simplicity and efficiency, more recent works found that the performance of the searched architecture barely increases with the optimization proceeding in DARTS, and the final magnitudes obtained by DARTS could hardly indicate the importance of operations.

Network Pruning Neural Architecture Search

Unsupervised Path Representation Learning with Curriculum Negative Sampling

1 code implementation17 Jun 2021 Sean Bin Yang, Chenjuan Guo, Jilin Hu, Jian Tang, Bin Yang

In the global view, PIM distinguishes the representations of the input paths from those of the negative paths.

Recommendation Systems Representation Learning

Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra

no code implementations1 Jun 2021 Kanil Patel, William Beluch, Kilian Rambach, Adriana-Eliza Cozma, Michael Pfeiffer, Bin Yang

Deep learning (DL) has recently attracted increasing interest to improve object type classification for automotive radar. In addition to high accuracy, it is crucial for decision making in autonomous vehicles to evaluate the reliability of the predictions; however, decisions of DL networks are non-transparent.

Autonomous Vehicles Decision Making +1

Contrastive Learning and Self-Training for Unsupervised Domain Adaptation in Semantic Segmentation

no code implementations5 May 2021 Robert A. Marsden, Alexander Bartler, Mario Döbler, Bin Yang

To avoid the costly annotation of training data for unseen domains, unsupervised domain adaptation (UDA) attempts to provide efficient knowledge transfer from a labeled source domain to an unlabeled target domain.

Contrastive Learning Semantic Segmentation +3

Intelligent Decision Method for Main Control Parameters of Tunnel Boring Machine based on Multi-Objective Optimization of Excavation Efficiency and Cost

no code implementations29 Apr 2021 Bin Liu, Yaxu Wang, Guangzu Zhao, Bin Yang, Ruirui Wang, Dexiang Huang, Bin Xiang

Therefore, this paper proposes an intelligent decision method for the main control parameters of the TBM based on the multi-objective optimization of excavation efficiency and cost.

Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full version

no code implementations19 Mar 2021 Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang

For example, speed sensors are deployed in different locations in a road network, where the speed of a specific location across time is captured by the corresponding sensor as a time series, resulting in multiple speed time series from different locations, which are often correlated.

Graph Attention Time Series +1

Uncertainty-Based Biological Age Estimation of Brain MRI Scans

no code implementations15 Mar 2021 Karim Armanious, Sherif Abdulatif, Wenbin Shi, Tobias Hepp, Sergios Gatidis, Bin Yang

We apply the proposed methodology on a brain MRI dataset containing healthy individuals as well as Alzheimer's patients.

Age Estimation

Anomaly Detection Based on Selection and Weighting in Latent Space

no code implementations8 Mar 2021 Yiwen Liao, Alexander Bartler, Bin Yang

Experiments on both benchmark and real-world datasets have shown the effectiveness and superiority of SWAD.

Anomaly Detection

Modelling brain based on canonical ensemble with functional MRI: A thermodynamic exploration on neural system

no code implementations26 Feb 2021 Chenxi Zhou, Bin Yang, Wenliang Fan, Wei Li

(3) The detection of neural disease was demonstrated to be benefit from thermodynamic model, implying the immense potential of thermodynamics in auxiliary diagnosis.

Condensed Composite Memory Continual Learning

1 code implementation19 Feb 2021 Felix Wiewel, Bin Yang

While many recently proposed methods for continual learning use some training examples for rehearsal, their performance strongly depends on the number of stored examples.

Continual Learning

SLPC: a VRNN-based approach for stochastic lidar prediction and completion in autonomous driving

no code implementations19 Feb 2021 George Eskandar, Alexander Braun, Martin Meinke, Karim Armanious, Bin Yang

Our algorithm is able to address the limitations of previous video prediction frameworks when dealing with sparse data by spatially inpainting the depth maps in the upcoming frames.

Autonomous Driving Decision Making +2

PLUMENet: Efficient 3D Object Detection from Stereo Images

1 code implementation17 Jan 2021 Yan Wang, Bin Yang, Rui Hu, Ming Liang, Raquel Urtasun

In this paper we propose a model that unifies these two tasks and performs them in the same metric space.

3D Object Detection 3D Object Detection From Stereo Images +2

Auto4D: Learning to Label 4D Objects from Sequential Point Clouds

no code implementations17 Jan 2021 Bin Yang, Min Bai, Ming Liang, Wenyuan Zeng, Raquel Urtasun

The key idea is to decompose the 4D object label into two parts: the object size in 3D that's fixed through time for rigid objects, and the motion path describing the evolution of the object's pose through time.

3D Object Detection

End-to-end Interpretable Neural Motion Planner

no code implementations CVPR 2019 Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun

In this paper, we propose a neural motion planner (NMP) for learning to drive autonomously in complex urban scenarios that include traffic-light handling, yielding, and interactions with multiple road-users.

Diverse Complexity Measures for Dataset Curation in Self-driving

no code implementations16 Jan 2021 Abbas Sadat, Sean Segal, Sergio Casas, James Tu, Bin Yang, Raquel Urtasun, Ersin Yumer

Our experiments on a wide range of tasks and models show that the proposed curation pipeline is able to select datasets that lead to better generalization and higher performance.

Active Learning Motion Forecasting

Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net

no code implementations CVPR 2018 Wenjie Luo, Bin Yang, Raquel Urtasun

In this paper we propose a novel deep neural network that is able to jointly reason about 3D detection, tracking and motion forecasting given data captured by a 3D sensor.

Motion Forecasting

HDNET: Exploiting HD Maps for 3D Object Detection

no code implementations21 Dec 2020 Bin Yang, Ming Liang, Raquel Urtasun

In this paper we show that High-Definition (HD) maps provide strong priors that can boost the performance and robustness of modern 3D object detectors.

3D Object Detection object-detection

Deep Continuous Fusion for Multi-Sensor 3D Object Detection

no code implementations ECCV 2018 Ming Liang, Bin Yang, Shenlong Wang, Raquel Urtasun

In this paper, we propose a novel 3D object detector that can exploit both LIDAR as well as cameras to perform very accurate localization.

3D Object Detection object-detection

Recovering and Simulating Pedestrians in the Wild

no code implementations16 Nov 2020 Ze Yang, Siva Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma, Raquel Urtasun

We then incorporate the reconstructed pedestrian assets bank in a realistic LiDAR simulation system by performing motion retargeting, and show that the simulated LiDAR data can be used to significantly reduce the amount of annotated real-world data required for visual perception tasks.

Data Augmentation motion retargeting

Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving

no code implementations2 Nov 2020 Bob Wei, Mengye Ren, Wenyuan Zeng, Ming Liang, Bin Yang, Raquel Urtasun

In this paper, we propose an end-to-end self-driving network featuring a sparse attention module that learns to automatically attend to important regions of the input.

Motion Planning

Feature Selection Using Batch-Wise Attenuation and Feature Mask Normalization

no code implementations26 Oct 2020 Yiwen Liao, Raphaël Latty, Bin Yang

Feature selection is generally used as one of the most important preprocessing techniques in machine learning, as it helps to reduce the dimensionality of data and assists researchers and practitioners in understanding data.

feature selection

Investigating Cross-Domain Losses for Speech Enhancement

no code implementations20 Oct 2020 Sherif Abdulatif, Karim Armanious, Jayasankar T. Sajeev, Karim Guirguis, Bin Yang

Recent years have seen a surge in the number of available frameworks for speech enhancement (SE) and recognition.

Speech Enhancement

V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction

1 code implementation ECCV 2020 Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wenyuan Zeng, James Tu, Raquel Urtasun

In this paper, we explore the use of vehicle-to-vehicle (V2V) communication to improve the perception and motion forecasting performance of self-driving vehicles.

3D Object Detection Motion Forecasting

DSDNet: Deep Structured self-Driving Network

no code implementations ECCV 2020 Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun

In this paper, we propose the Deep Structured self-Driving Network (DSDNet), which performs object detection, motion prediction, and motion planning with a single neural network.

Motion Planning motion prediction +2

Force myography benchmark data for hand gesture recognition and transfer learning

1 code implementation29 Jul 2020 Thomas Buhl Andersen, Rógvi Eliasen, Mikkel Jarlund, Bin Yang

We contribute to the advancement of this field by making accessible a benchmark dataset collected using a commercially available sensor setup from 20 persons covering 18 unique gestures, in the hope of allowing further comparison of results as well as easier entry into this field of research.

Hand Gesture Recognition Hand-Gesture Recognition +1

RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects

no code implementations ECCV 2020 Bin Yang, Runsheng Guo, Ming Liang, Sergio Casas, Raquel Urtasun

We tackle the problem of exploiting Radar for perception in the context of self-driving as Radar provides complementary information to other sensors such as LiDAR or cameras in the form of Doppler velocity.

object-detection Object Detection

Learning Lane Graph Representations for Motion Forecasting

1 code implementation ECCV 2020 Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun

We propose a motion forecasting model that exploits a novel structured map representation as well as actor-map interactions.

Motion Forecasting Trajectory Prediction

Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning

1 code implementation ICLR 2021 Kanil Patel, William Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang

The goal of this paper is to resolve the identified issues of HB in order to provide calibrated confidence estimates using only a small holdout calibration dataset for bin optimization while preserving multi-class ranking accuracy.


LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World

no code implementations CVPR 2020 Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Shuhan Tan, Bin Yang, Wei-Chiu Ma, Raquel Urtasun

We first utilize ray casting over the 3D scene and then use a deep neural network to produce deviations from the physics-based simulation, producing realistic LiDAR point clouds.

Physically Realizable Adversarial Examples for LiDAR Object Detection

no code implementations CVPR 2020 James Tu, Mengye Ren, Siva Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun

Modern autonomous driving systems rely heavily on deep learning models to process point cloud sensory data; meanwhile, deep models have been shown to be susceptible to adversarial attacks with visually imperceptible perturbations.

Adversarial Defense Autonomous Driving +3

Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes

no code implementations26 Feb 2020 Jilin Hu, Jianbing Shen, Bin Yang, Ling Shao

Graph convolutional neural networks~(GCNs) have recently demonstrated promising results on graph-based semi-supervised classification, but little work has been done to explore their theoretical properties.

Gaussian Processes General Classification

On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration

no code implementations16 Dec 2019 Kanil Patel, William Beluch, Dan Zhang, Michael Pfeiffer, Bin Yang

Uncertainty estimates help to identify ambiguous, novel, or anomalous inputs, but the reliable quantification of uncertainty has proven to be challenging for modern deep networks.

Adversarial Attack Data Augmentation

ipA-MedGAN: Inpainting of Arbitrary Regions in Medical Imaging

no code implementations21 Oct 2019 Karim Armanious, Vijeth Kumar, Sherif Abdulatif, Tobias Hepp, Sergios Gatidis, Bin Yang

Local deformations in medical modalities are common phenomena due to a multitude of factors such as metallic implants or limited field of views in magnetic resonance imaging (MRI).

Image Inpainting

AeGAN: Time-Frequency Speech Denoising via Generative Adversarial Networks

no code implementations21 Oct 2019 Sherif Abdulatif, Karim Armanious, Karim Guirguis, Jayasankar T. Sajeev, Bin Yang

Automatic speech recognition (ASR) systems are of vital importance nowadays in commonplace tasks such as speech-to-text processing and language translation.

Automatic Speech Recognition Denoising +3

Organ-based Chronological Age Estimation based on 3D MRI Scans

no code implementations14 Oct 2019 Karim Armanious, Sherif Abdulatif, Anish Rao Bhaktharaguttu, Thomas Küstner, Tobias Hepp, Sergios Gatidis, Bin Yang

Individuals age differently depending on a multitude of different factors such as lifestyle, medical history and genetics.

Age Estimation

Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media Images

1 code implementation9 Aug 2019 Björn Barz, Kai Schröter, Moritz Münch, Bin Yang, Andrea Unger, Doris Dransch, Joachim Denzler

The analysis of natural disasters such as floods in a timely manner often suffers from limited data due to a coarse distribution of sensors or sensor failures.

Content-Based Image Retrieval

PathRank: A Multi-Task Learning Framework to Rank Paths in Spatial Networks

no code implementations9 Jul 2019 Sean Bin Yang, Bin Yang

The objective function is designed to consider errors on both ranking scores and spatial properties, making the framework a multi-task learning framework.

Multi-Task Learning Network Embedding

Localizing Catastrophic Forgetting in Neural Networks

no code implementations6 Jun 2019 Felix Wiewel, Bin Yang

Artificial neural networks (ANNs) suffer from catastrophic forgetting when trained on a sequence of tasks.

Continual Learning

Unsupervised Medical Image Translation Using Cycle-MedGAN

no code implementations8 Mar 2019 Karim Armanious, Chenming Jiang, Sherif Abdulatif, Thomas Küstner, Sergios Gatidis, Bin Yang

The proposed framework utilizes new non-adversarial cycle losses which direct the framework to minimize the textural and perceptual discrepancies in the translated images.

Image-to-Image Translation Translation

An Adversarial Super-Resolution Remedy for Radar Design Trade-offs

no code implementations4 Mar 2019 Karim Armanious, Sherif Abdulatif, Fady Aziz, Urs Schneider, Bin Yang

Radar is of vital importance in many fields, such as autonomous driving, safety and surveillance applications.

Autonomous Driving Super-Resolution

Active Learning for One-Class Classification Using Two One-Class Classifiers

no code implementations10 Jan 2019 Patrick Schlachter, Bin Yang

Active learning methods play an important role to reduce the efforts of manual labeling in the field of machine learning.

Active Learning General Classification

One-Class Feature Learning Using Intra-Class Splitting

no code implementations20 Dec 2018 Patrick Schlachter, Yiwen Liao, Bin Yang

This paper proposes a novel generic one-class feature learning method based on intra-class splitting.

Classification General Classification +1

Non-invasive measuring method of skin temperature based on skin sensitivity index and deep learning

no code implementations16 Dec 2018 Xiaogang Cheng, Bin Yang, Kaige Tan, Erik Isaksson, Liren Li, Anders Hedman, Thomas Olofsson, Hai-Bo Li

Due to the challenges of intra- and inter-individual differences and skin subtleness variations, there is no satisfactory solution for thermal comfort measurements until now.

Person Identification and Body Mass Index: A Deep Learning-Based Study on Micro-Dopplers

no code implementations17 Nov 2018 Sherif Abdulatif, Fady Aziz, Karim Armanious, Bernhard Kleiner, Bin Yang, Urs Schneider

In our proposed experimental setup, a treadmill is used to collect $\boldsymbol{\mu}$-D signatures of 22 subjects with different genders and body characteristics.

Person Identification

Recurrent Multi-Graph Neural Networks for Travel Cost Prediction

no code implementations13 Nov 2018 Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen, Lu Chen

Origin-destination (OD) matrices are often used in urban planning, where a city is partitioned into regions and an element (i, j) in an OD matrix records the cost (e. g., travel time, fuel consumption, or travel speed) from region i to region j.

Towards Adversarial Denoising of Radar Micro-Doppler Signatures

no code implementations12 Nov 2018 Sherif Abdulatif, Karim Armanious, Fady Aziz, Urs Schneider, Bin Yang

Two sets of experiments were collected on 22 subjects walking on a treadmill at an intermediate velocity using a \unit[25]{GHz} CW radar.

Denoising Denoising Of Radar Micro-Doppler Signatures +1

Deep Neural Network inference with reduced word length

no code implementations23 Oct 2018 Lukas Mauch, Bin Yang

Deep neural networks (DNN) are powerful models for many pattern recognition tasks, yet their high computational complexity and memory requirement limit them to applications on high-performance computing platforms.

Retrospective correction of Rigid and Non-Rigid MR motion artifacts using GANs

no code implementations17 Sep 2018 Karim Armanious, Sergios Gatidis, Konstantin Nikolaou, Bin Yang, Thomas Küstner

Motion artifacts are a primary source of magnetic resonance (MR) image quality deterioration with strong repercussions on diagnostic performance.

Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results

no code implementations29 Aug 2018 Razvan-Gabriel Cirstea, Darius-Valer Micu, Gabriel-Marcel Muresan, Chenjuan Guo, Bin Yang

To enable accurate forecasting on such correlated time series, this paper proposes two models that combine convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

Multi-Task Learning Time Series +1

MedGAN: Medical Image Translation using GANs

1 code implementation17 Jun 2018 Karim Armanious, Chenming Jiang, Marc Fischer, Thomas Küstner, Konstantin Nikolaou, Sergios Gatidis, Bin Yang

Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications.

Image Denoising Image-to-Image Translation +2

Learning to Reweight Examples for Robust Deep Learning

9 code implementations ICML 2018 Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun

Deep neural networks have been shown to be very powerful modeling tools for many supervised learning tasks involving complex input patterns.


Multi-level Attention Model for Weakly Supervised Audio Classification

5 code implementations6 Mar 2018 Changsong Yu, Karim Said Barsim, Qiuqiang Kong, Bin Yang

The objective of audio classification is to predict the presence or absence of audio events in an audio clip.

Audio Classification Classification

Learning to Route with Sparse Trajectory Sets---Extended Version

no code implementations22 Feb 2018 Chenjuan Guo, Bin Yang, Jilin Hu, Christian S. Jensen

In the second step, we exploit the above graph-like structure to achieve a comprehensive trajectory-based routing solution.

Neural Network Ensembles to Real-time Identification of Plug-level Appliance Measurements

no code implementations20 Feb 2018 Karim Said Barsim, Lukas Mauch, Bin Yang

The problem of identifying end-use electrical appliances from their individual consumption profiles, known as the appliance identification problem, is a primary stage in both Non-Intrusive Load Monitoring (NILM) and automated plug-wise metering.

Non-Intrusive Load Monitoring

On the Feasibility of Generic Deep Disaggregation for Single-Load Extraction

no code implementations5 Feb 2018 Karim Said Barsim, Bin Yang

Recently, and with the growing development of big energy datasets, data-driven learning techniques began to represent a potential solution to the energy disaggregation problem outperforming engineered and hand-crafted models.

Selective Sampling and Mixture Models in Generative Adversarial Networks

no code implementations2 Feb 2018 Karim Said Barsim, Lirong Yang, Bin Yang

In this paper, we propose a multi-generator extension to the adversarial training framework, in which the objective of each generator is to represent a unique component of a target mixture distribution.

SBNet: Sparse Blocks Network for Fast Inference

2 code implementations CVPR 2018 Mengye Ren, Andrei Pokrovsky, Bin Yang, Raquel Urtasun

Conventional deep convolutional neural networks (CNNs) apply convolution operators uniformly in space across all feature maps for hundreds of layers - this incurs a high computational cost for real-time applications.

3D Object Detection object-detection +1

TorontoCity: Seeing the World with a Million Eyes

no code implementations ICCV 2017 Shenlong Wang, Min Bai, Gellert Mattyus, Hang Chu, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun

In this paper we introduce the TorontoCity benchmark, which covers the full greater Toronto area (GTA) with 712. 5 $km^2$ of land, 8439 $km$ of road and around 400, 000 buildings.

Instance Segmentation Semantic Segmentation

Crafting GBD-Net for Object Detection

1 code implementation8 Oct 2016 Xingyu Zeng, Wanli Ouyang, Junjie Yan, Hongsheng Li, Tong Xiao, Kun Wang, Yu Liu, Yucong Zhou, Bin Yang, Zhe Wang, Hui Zhou, Xiaogang Wang

The effectiveness of GBD-Net is shown through experiments on three object detection datasets, ImageNet, Pascal VOC2007 and Microsoft COCO.

object-detection Object Detection

CRAFT Objects from Images

1 code implementation CVPR 2016 Bin Yang, Junjie Yan, Zhen Lei, Stan Z. Li

They decompose the object detection problem into two cascaded easier tasks: 1) generating object proposals from images, 2) classifying proposals into various object categories.

object-detection Object Detection +1

Convolutional Channel Features

1 code implementation ICCV 2015 Bin Yang, Junjie Yan, Zhen Lei, Stan Z. Li

With the combination of CNN features and boosting forest, CCF benefits from the richer capacity in feature representation compared with channel features, as well as lower cost in computation and storage compared with end-to-end CNN methods.

Edge Detection Face Detection +2

Aggregate channel features for multi-view face detection

no code implementations15 Jul 2014 Bin Yang, Junjie Yan, Zhen Lei, Stan Z. Li

Face detection has drawn much attention in recent decades since the seminal work by Viola and Jones.

Face Detection Re-Ranking

Connectivity for matroids based on rough sets

no code implementations5 Nov 2013 Bin Yang, William Zhu

Second, we study the connectivity for matroids by means of relation-based rough sets and some conditions under which a general matroid is connected are presented.

Rough matroids based on coverings

no code implementations2 Nov 2013 Bin Yang, Hong Zhao, William Zhu

First, we investigate some properties of the definable sets with respect to a covering.

Combinatorial Optimization

Using Incomplete Information for Complete Weight Annotation of Road Networks -- Extended Version

no code implementations2 Aug 2013 Bin Yang, Manohar Kaul, Christian S. Jensen

This paper formulates and addresses the problem of annotating all edges in a road network with travel cost based weights from a set of trips in the network that cover only a small fraction of the edges, each with an associated ground-truth travel cost.

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