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Shearlets as Feature Extractor for Semantic Edge Detection: The Model-Based and Data-Driven Realm
Semantic edge detection has recently gained a lot of attention as an ima...
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Kernel of CycleGAN as a Principle homogeneous space
Unpaired image-to-image translation has attracted significant interest d...
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Deep Bayesian Inversion
Characterizing statistical properties of solutions of inverse problems i...
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Human-centered collaborative robots with deep reinforcement learning
We present a reinforcement learning based framework for human-centered c...
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Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast Cancer Risk Models
The ability to accurately estimate risk of developing breast cancer woul...
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The Importance of Balanced Data Sets: Analyzing a Vehicle Trajectory Prediction Model based on Neural Networks and Distributed Representations
Predicting future behavior of other traffic participants is an essential...
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Which way? Direction-Aware Attributed Graph Embedding
Graph embedding algorithms are used to efficiently represent (encode) a ...
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Imitating by generating: deep generative models for imitation of interactive tasks
To coordinate actions with an interaction partner requires a constant ex...
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Neural Outlier Rejection for Self-Supervised Keypoint Learning
Identifying salient points in images is a crucial component for visual o...
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Finite-time Identification of Stable Linear Systems: Optimality of the Least-Squares Estimator
We provide a new finite-time analysis of the estimation error of stable ...
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Coordinates-based Resource Allocation Through Supervised Machine Learning
Appropriate allocation of system resources is essential for meeting the ...
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GCNv2: Efficient Correspondence Prediction for Real-Time SLAM
In this paper, we present a deep learning-based network, GCNv2, for gene...
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Machine Learning assisted Handover and Resource Management for Cellular Connected Drones
Enabling cellular connectivity for drones introduces a wide set of chall...
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Analyzing the Capacity of Distributed Vector Representations to Encode Spatial Information
Vector Symbolic Architectures belong to a family of related cognitive mo...
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Hyperplane Arrangements of Trained ConvNets Are Biased
We investigate the geometric properties of the functions learned by trai...
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α Belief Propagation for Approximate Inference
Belief propagation (BP) algorithm is a widely used message-passing metho...
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Beyond the Self: Using Grounded Affordances to Interpret and Describe Others' Actions
We propose a developmental approach that allows a robot to interpret and...
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Sparse2Dense: From direct sparse odometry to dense 3D reconstruction
In this paper, we proposed a new deep learning based dense monocular SLA...
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A Framework for Depth Estimation and Relative Localization of Ground Robots using Computer Vision
The 3D depth estimation and relative pose estimation problem within a de...
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Neural Network based Explicit Mixture Models and Expectation-maximization based Learning
We propose two neural network based mixture models in this article. The ...
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Tighter expected generalization error bounds via Wasserstein distance
In this work, we introduce several expected generalization error bounds ...
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Entropy-regularized Optimal Transport Generative Models
We investigate the use of entropy-regularized optimal transport (EOT) co...
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A Hierarchical Grocery Store Image Dataset with Visual and Semantic Labels
Image classification models built into visual support systems and other ...
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Explanation-based Weakly-supervised Learning of Visual Relations with Graph Networks
Visual relationship detection is fundamental for holistic image understa...
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Incremental inference of collective graphical models
We consider incremental inference problems from aggregate data for colle...
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α Belief Propagation as Fully Factorized Approximation
Belief propagation (BP) can do exact inference in loop-free graphs, but ...
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Bayesian nonparametric shared multi-sequence time series segmentation
In this paper, we introduce a method for segmenting time series data usi...
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Banach Wasserstein GAN
Wasserstein Generative Adversarial Networks (WGANs) can be used to gener...
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Optimal Attacks on Reinforcement Learning Policies
Control policies, trained using the Deep Reinforcement Learning, have be...
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A Survey of Behavior Trees in Robotics and AI
Behavior Trees (BTs) were invented as a tool to enable modular AI in com...
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Distributed sampled-data control of nonholonomic multi-robot systems with proximity networks
This paper considers the distributed sampled-data control problem of a g...
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Interactive Robot Learning of Gestures, Language and Affordances
A growing field in robotics and Artificial Intelligence (AI) research is...
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Self-Supervised Vision-Based Detection of the Active Speaker as a Prerequisite for Socially-Aware Language Acquisition
This paper presents a self-supervised method for detecting the active sp...
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Minimal Exploration in Structured Stochastic Bandits
This paper introduces and addresses a wide class of stochastic bandit pr...
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Advances in Variational Inference
Many modern unsupervised or semi-supervised machine learning algorithms ...
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Learned Primal-dual Reconstruction
We propose the Learned Primal-Dual algorithm for tomographic reconstruct...
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Machine Learning and Social Robotics for Detecting Early Signs of Dementia
This paper presents the EACare project, an ambitious multi-disciplinary ...
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On the Performance of Network Parallel Training in Artificial Neural Networks
Artificial Neural Networks (ANNs) have received increasing attention in ...
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Learning to solve inverse problems using Wasserstein loss
We propose using the Wasserstein loss for training in inverse problems. ...
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Unsupervised Object Discovery and Segmentation of RGBD-images
In this paper we introduce a system for unsupervised object discovery an...
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Dynamic texture recognition using time-causal and time-recursive spatio-temporal receptive fields
This work presents a first evaluation of using spatio-temporal receptive...
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Optimising The Input Window Alignment in CD-DNN Based Phoneme Recognition for Low Latency Processing
We present a systematic analysis on the performance of a phonetic recogn...
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Dense scale selection over space, time and space-time
Scale selection methods based on local extrema over scale of scale-norma...
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Fitting Generalized Essential Matrices from Generic 6x6 Matrices and its Applications
This paper addresses the problem of finding the closest generalized esse...
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A Connectedness Constraint for Learning Sparse Graphs
Graphs are naturally sparse objects that are used to study many problems...
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Solving ill-posed inverse problems using iterative deep neural networks
We propose a partially learned approach for the solution of ill posed in...
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Determinantal Point Processes for Mini-Batch Diversification
We study a mini-batch diversification scheme for stochastic gradient des...
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cGAN-based Manga Colorization Using a Single Training Image
The Japanese comic format known as Manga is popular all over the world. ...
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Indirect Image Registration with Large Diffeomorphic Deformations
The paper adapts the large deformation diffeomorphic metric mapping fram...
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Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection
Despite significant progress in the development of human action detectio...
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