b'DLR'

research

∙ 09/23/2021

Bridging the Last Mile in Sim-to-Real Robot Perception via Bayesian Active Learning

Learning from synthetic data is popular in a variety of robotic vision t...

Jianxiang Feng, et al. ∙

research

∙ 01/23/2019

ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features

With the rapid development of spaceborne imaging techniques, object dete...

Xin Wu, et al. ∙

research

∙ 12/18/2019

Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification

Up to the present, an enormous number of advanced techniques have been d...

Danfeng Hong, et al. ∙

research

∙ 06/27/2022

Self-supervised Learning in Remote Sensing: A Review

In deep learning research, self-supervised learning (SSL) has received g...

Yi Wang, et al. ∙

research

∙ 12/30/2018

CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences

With a large amount of open satellite multispectral imagery (e.g., Senti...

Danfeng Hong, et al. ∙

research

∙ 01/30/2020

ERA: A Dataset and Deep Learning Benchmark for Event Recognition in Aerial Videos

Along with the increasing use of unmanned aerial vehicles (UAVs), large ...

Lichao Mou, et al. ∙

research

∙ 01/17/2022

Disentangled Latent Transformer for Interpretable Monocular Height Estimation

Monocular height estimation (MHE) from remote sensing imagery has high p...

Zhitong Xiong Sining Chen, et al. ∙

research

∙ 02/04/2020

Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

In this paper, we propose an efficient and effective framework to fuse h...

Renlong Hang, et al. ∙

research

∙ 08/23/2019

A Review of Point Cloud Semantic Segmentation

3D Point Cloud Semantic Segmentation (PCSS) is attracting increasing int...

Yuxing Xie, et al. ∙

research

∙ 03/23/2022

DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation

Earth observation is a fundamental tool for monitoring the evolution of ...

Aysim Toker, et al. ∙

research

∙ 03/02/2021

HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline

Deep learning-based coastline detection algorithms have begun to outshin...

Konrad Heidler, et al. ∙

research

∙ 07/04/2021

Leveraging Evidential Deep Learning Uncertainties with Graph-based Clustering to Detect Anomalies

Understanding and representing traffic patterns are key to detecting ano...

Sandeep Kumar Singh, et al. ∙

research

∙ 01/31/2022

AutoGeoLabel: Automated Label Generation for Geospatial Machine Learning

A key challenge of supervised learning is the availability of human-labe...

Conrad M Albrecht, et al. ∙

research

∙ 02/28/2019

Cascaded Recurrent Neural Networks for Hyperspectral Image Classification

By considering the spectral signature as a sequence, recurrent neural ne...

Renlong Hang, et al. ∙

research

∙ 05/18/2022

A2C is a special case of PPO

Advantage Actor-critic (A2C) and Proximal Policy Optimization (PPO) are ...

Shengyi Huang, et al. ∙

research

∙ 07/30/2018

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...

Yuansheng Hua, et al. ∙

research

∙ 02/04/2019

Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

We propose a real-time RGB-based pipeline for object detection and 6D po...

Martin Sundermeyer, et al. ∙

research

∙ 05/18/2020

Cross-Task Transfer for Multimodal Aerial Scene Recognition

Aerial scene recognition is a fundamental task in remote sensing and has...

Di Hu, et al. ∙

research

∙ 06/13/2019

MIMA: MAPPER-Induced Manifold Alignment for Semi-Supervised Fusion of Optical Image and Polarimetric SAR Data

Multi-modal data fusion has recently been shown promise in classificatio...

Jingliang Hu, et al. ∙

research

∙ 02/24/2021

Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges

In the past decade, object detection has achieved significant progress i...

Jian Ding, et al. ∙

research

∙ 12/30/2021

THE Benchmark: Transferable Representation Learning for Monocular Height Estimation

Generating 3D city models rapidly is crucial for many applications. Mono...

Zhitong Xiong, et al. ∙

research

∙ 08/02/2021

Self-supervised Audiovisual Representation Learning for Remote Sensing Data

Many current deep learning approaches make extensive use of backbone net...

Konrad Heidler, et al. ∙

research

∙ 12/06/2021

SyntEO: Synthetic Dataset Generation for Earth Observation with Deep Learning – Demonstrated for Offshore Wind Farm Detection

With the emergence of deep learning in the last years, new opportunities...

Thorsten Hoeser, et al. ∙

research

∙ 04/05/2018

End-to-End Saliency Mapping via Probability Distribution Prediction

Most saliency estimation methods aim to explicitly model low-level consp...

Saumya Jetley, et al. ∙

research

∙ 08/16/2018

R^3-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos

Vehicle detection is a significant and challenging task in aerial remote...

Qingpeng Li, et al. ∙

research

∙ 07/24/2019

Heat Transfer Prediction for Methane in Regenerative Cooling Channels with Neural Networks

Methane is considered being a good choice as a propellant for future reu...

Günther Waxenegger-Wilfing, et al. ∙

research

∙ 08/03/2021

Research Challenges and Progress in Robotic Grasping and Manipulation Competitions

This paper discusses recent research progress in robotic grasping and ma...

Yu Sun, et al. ∙

research

∙ 07/04/2022

Location reference recognition from texts: A survey and comparison

A vast amount of location information exists in unstructured texts, such...

Xuke Hu, et al. ∙

research

∙ 03/25/2020

Visual-Inertial Telepresence for Aerial Manipulation

This paper presents a novel telepresence system for enhancing aerial man...

Jongseok Lee, et al. ∙

research

∙ 02/01/2022

A Model for Multi-View Residual Covariances based on Perspective Deformation

In this work, we derive a model for the covariance of the visual residua...

Alejandro Fontan, et al. ∙

research

∙ 11/28/2017

DOTA: A Large-scale Dataset for Object Detection in Aerial Images

Object detection is an important and challenging problem in computer vis...

Gui-Song Xia, et al. ∙

research

∙ 09/11/2017

Cellular Automaton Based Simulation of Large Pedestrian Facilities - A Case Study on the Staten Island Ferry Terminals

Current metropolises largely depend on a functioning transport infrastru...

Luca Crociani, et al. ∙

research

∙ 10/11/2017

Deep learning in remote sensing: a review

Standing at the paradigm shift towards data-intensive science, machine l...

Xiao Xiang Zhu, et al. ∙

research

∙ 05/20/2016

Virtual Worlds as Proxy for Multi-Object Tracking Analysis

Modern computer vision algorithms typically require expensive data acqui...

Adrien Gaidon, et al. ∙

research

∙ 07/23/2017

Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation

Remote sensing (RS) image retrieval based on visual content is of great ...

Gui-Song Xia, et al. ∙

research

∙ 12/12/2016

Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks

We propose an inverse reinforcement learning (IRL) approach using Deep Q...

Sahand Sharifzadeh, et al. ∙

research

∙ 09/09/2011

Learning Sequence Neighbourhood Metrics

Recurrent neural networks (RNNs) in combination with a pooling operator ...

Justin Bayer, et al. ∙

research

∙ 12/05/2016

Classification With an Edge: Improving Semantic Image Segmentation with Boundary Detection

We present an end-to-end trainable deep convolutional neural network (DC...

Dimitrios Marmanis, et al. ∙

research

∙ 08/25/2016

Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition

Action recognition in videos is a challenging task due to the complexity...

César Roberto de Souza, et al. ∙

research

∙ 02/14/2014

Authorship Analysis based on Data Compression

This paper proposes to perform authorship analysis using the Fast Compre...

Daniele Cerra, et al. ∙

research

∙ 04/03/2012

Application of Bayesian Hierarchical Prior Modeling to Sparse Channel Estimation

Existing methods for sparse channel estimation typically provide an esti...

Niels Lovmand Pedersen, et al. ∙

research

∙ 08/22/2011

Sparse Estimation using Bayesian Hierarchical Prior Modeling for Real and Complex Linear Models

In sparse Bayesian learning (SBL), Gaussian scale mixtures (GSMs) have b...

Niels Lovmand Pedersen, et al. ∙

research

∙ 08/05/2002

Probabilistic Search for Object Segmentation and Recognition

The problem of searching for a model-based scene interpretation is analy...

Ulrich Hillenbrand, et al. ∙

research

∙ 01/17/2018

On Decoding Schemes for the MDPC-McEliece Cryptosystem

Recently, it has been shown how McEliece public-key cryptosystems based ...

Hannes Bartz, et al. ∙

research

∙ 01/23/2018

Protograph-based Quasi-Cyclic MDPC Codes for McEliece Cryptosystems

In this paper, ensembles of quasi-cyclic moderate-density parity-check (...

Gianluigi Liva, et al. ∙

research

∙ 01/25/2018

Identifying Corresponding Patches in SAR and Optical Images with a Pseudo-Siamese CNN

In this letter, we propose a pseudo-siamese convolutional neural network...

Lloyd H. Hughes, et al. ∙

research

∙ 02/05/2018

Road Segmentation in SAR Satellite Images with Deep Fully-Convolutional Neural Networks

Remote sensing is extensively used in cartography. As transportation net...

Corentin Henry, et al. ∙

research

∙ 02/15/2018

Improving the Decoding Threshold of Tailbiting Spatially Coupled LDPC Codes by Energy Shaping

We show how the iterative decoding threshold of tailbiting spatially cou...

Thomas Jerkovits, et al. ∙

research

∙ 02/28/2018

IM2HEIGHT: Height Estimation from Single Monocular Imagery via Fully Residual Convolutional-Deconvolutional Network

In this paper we tackle a very novel problem, namely height estimation f...

Lichao Mou, et al. ∙

research

∙ 03/04/2018

Finite Length Analysis of Irregular Repetition Slotted ALOHA in the Waterfall Region

A finite length analysis is introduced for irregular repetition slotted ...

Alexandre Graell i Amat, et al. ∙

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