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A Comparative Study between Bayesian and Frequentist Neural Networks for Remaining Useful Life Estimation in Condition-Based Maintenance
In the last decade, deep learning (DL) has outperformed model-based and ...
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Machine Learning-Based Optimal Mesh Generation in Computational Fluid Dynamics
Computational Fluid Dynamics (CFD) is a major sub-field of engineering. ...
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Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient
In this study, we explore quantitative correlates of qualitative human e...
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Autolabeling 3D Objects with Differentiable Rendering of SDF Shape Priors
We present an automatic annotation pipeline to recover 9D cuboids and 3D...
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Adversarial Convolutional Networks with Weak Domain-Transfer for Multi-Sequence Cardiac MR Images Segmentation
Analysis and modeling of the ventricles and myocardium are important in ...
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WeatherBench: A benchmark dataset for data-driven weather forecasting
Data-driven approaches, most prominently deep learning, have become powe...
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Predictive Collective Variable Discovery with Deep Bayesian Models
Extending spatio-temporal scale limitations of models for complex atomis...
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clDice – a Topology-Preserving Loss Function for Tubular Structure Segmentation
Accurate segmentation of tubular, network-like structures, such as vesse...
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Hierarchical Feature Embedding for Attribute Recognition
Attribute recognition is a crucial but challenging task due to viewpoint...
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Generalized Zero and Few-Shot Transfer for Facial Forgery Detection
We propose Deep Distribution Transfer(DDT), a new transfer learning appr...
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e-UDA: Efficient Unsupervised Domain Adaptation for Cross-Site Medical Image Segmentation
Domain adaptation in healthcare data is a potentially critical component...
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ERA: A Dataset and Deep Learning Benchmark for Event Recognition in Aerial Videos
Along with the increasing use of unmanned aerial vehicles (UAVs), large ...
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A Deep Learning-based Radar and Camera Sensor Fusion Architecture for Object Detection
Object detection in camera images, using deep learning has been proven s...
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Learning a Neural Solver for Multiple Object Tracking
Graphs offer a natural way to formulate Multiple Object Tracking (MOT) w...
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FutureGAN: Anticipating the Future Frames of Video Sequences using Spatio-Temporal 3d Convolutions in Progressively Growing Autoencoder GANs
We propose a new Autoencoder GAN model, FutureGAN, that predicts future ...
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SteReFo: Efficient Image Refocusing with Stereo Vision
Whether to attract viewer attention to a particular object, give the imp...
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Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach
A novel approach towards depth map super-resolution using multi-view unc...
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Learning Graph Embeddings for Compositional Zero-shot Learning
In compositional zero-shot learning, the goal is to recognize unseen com...
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MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification
We introduce MultiDepth, a novel training strategy and convolutional neu...
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Planning from Images with Deep Latent Gaussian Process Dynamics
Planning is a powerful approach to control problems with known environme...
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CorNet: Generic 3D Corners for 6D Pose Estimation of New Objects without Retraining
We present a novel approach to the detection and 3D pose estimation of o...
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HistoNet: Predicting size histograms of object instances
We propose to predict histograms of object sizes in crowded scenes direc...
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Ultrasound-Guided Robotic Navigation with Deep Reinforcement Learning
In this paper we introduce the first reinforcement learning (RL) based r...
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Parsing Geometry Using Structure-Aware Shape Templates
Real-life man-made objects often exhibit strong and easily-identifiable ...
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An Optical Flow-Based Approach for Minimally-Divergent Velocimetry Data Interpolation
Three-dimensional (3D) biomedical image sets are often acquired with in-...
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Tracking without bells and whistles
The problem of tracking multiple objects in a video sequence poses sever...
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Scalable Deep Learning on Distributed Infrastructures: Challenges, Techniques and Tools
Deep Learning (DL) has had an immense success in the recent past, leadin...
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Generating Reliable Process Event Streams and Time Series Data based on Neural Networks
Domains such as manufacturing and medicine crave for continuous monitori...
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A Review on Neural Network Models of Schizophrenia and Autism Spectrum Disorder
This survey presents the most relevant neural network models of autism s...
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Force-Ultrasound Fusion: Bringing Spine Robotic-US to the Next "Level"
Spine injections are commonly performed in several clinical procedures. ...
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Spatiotemporal-Aware Augmented Reality: Redefining HCI in Image-Guided Therapy
Suboptimal interaction with patient data and challenges in mastering 3D ...
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Indirect and Direct Training of Spiking Neural Networks for End-to-End Control of a Lane-Keeping Vehicle
Building spiking neural networks (SNNs) based on biological synaptic pla...
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Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation
Segmentation of Multiple Sclerosis (MS) lesions in longitudinal brain MR...
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Recurrently Exploring Class-wise Attention in A Hybrid Convolutional and Bidirectional LSTM Network for Multi-label Aerial Image Classification
Aerial image classification is of great significance in remote sensing c...
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CVPR19 Tracking and Detection Challenge: How crowded can it get?
Standardized benchmarks are crucial for the majority of computer vision ...
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Object-Driven Multi-Layer Scene Decomposition From a Single Image
We present a method that tackles the challenge of predicting color and d...
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Self6D: Self-Supervised Monocular 6D Object Pose Estimation
Estimating the 6D object pose is a fundamental problem in computer visio...
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Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective
Exploiting learning algorithms under scarce data regimes is a limitation...
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Decision Support for Intoxication Prediction Using Graph Convolutional Networks
Every day, poison control centers (PCC) are called for immediate classif...
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Cross-Task Transfer for Multimodal Aerial Scene Recognition
Aerial scene recognition is a fundamental task in remote sensing and has...
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From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds
We propose a new method for segmentation-free joint estimation of orthog...
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Multi-Source Neural Variational Inference
Learning from multiple sources of information is an important problem in...
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Temporally Coherent GANs for Video Super-Resolution (TecoGAN)
Adversarial training has been highly successful in the context of image ...
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Deferred Neural Rendering: Image Synthesis using Neural Textures
The modern computer graphics pipeline can synthesize images at remarkabl...
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Towards Unsupervised Image Captioning with Shared Multimodal Embeddings
Understanding images without explicit supervision has become an importan...
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Deep Model-Based 6D Pose Refinement in RGB
We present a novel approach for model-based 6D pose refinement in color ...
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Real-Time Driver State Monitoring Using a CNN Based Spatio-Temporal Approach
Many road accidents occur due to distracted drivers. Today, driver monit...
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GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation
6D pose estimation from a single RGB image is a fundamental task in comp...
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Omnidirectional DSO: Direct Sparse Odometry with Fisheye Cameras
We propose a novel real-time direct monocular visual odometry for omnidi...
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SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again
We present a novel method for detecting 3D model instances and estimatin...
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