research
∙
04/04/2023
Multi-Channel Time-Series Person and Soft-Biometric Identification
Multi-channel time-series datasets are popular in the context of human a...
share
research
∙
01/19/2023
Dataset Bias in Human Activity Recognition
When creating multi-channel time-series datasets for Human Activity Reco...
research
∙
12/02/2022
Video-based Pose-Estimation Data as Source for Transfer Learning in Human Activity Recognition
Human Activity Recognition (HAR) using on-body devices identifies specif...
research
∙
06/07/2022
Self-Training of Handwritten Word Recognition for Synthetic-to-Real Adaptation
Performances of Handwritten Text Recognition (HTR) models are largely de...
research
∙
02/12/2022
Recognition-free Question Answering on Handwritten Document Collections
In recent years, considerable progress has been made in the research are...
research
∙
01/31/2022
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs
We present an approach to quantifying both aleatoric and epistemic uncer...
research
∙
05/14/2020
Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation
When deploying deep learning technology in self-driving cars, deep neura...
research
∙
03/04/2020
Annotation-free Learning of Deep Representations for Word Spotting using Synthetic Data and Self Labeling
Word spotting is a popular tool for supporting the first exploration of ...
research
∙
03/26/2019
Exploring Confidence Measures for Word Spotting in Heterogeneous Datasets
In recent years, convolutional neural networks (CNNs) took over the fiel...
research
∙
06/28/2018
Expolring Architectures for CNN-Based Word Spotting
The goal in word spotting is to retrieve parts of document images which ...
research
∙
02/02/2018
Learning Attribute Representation for Human Activity Recognition
Attribute representations became relevant in image recognition and word ...
research
∙
01/26/2018
Weakly Supervised Object Detection with Pointwise Mutual Information
In this work a novel approach for weakly supervised object detection tha...
research
∙
12/01/2017
Learning Deep Representations for Word Spotting Under Weak Supervision
Convolutional Neural Networks have made their mark in various fields of ...
research
∙
07/21/2017
Neuron Pruning for Compressing Deep Networks using Maxout Architectures
This paper presents an efficient and robust approach for reducing the si...
research
∙
06/29/2017
Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus images
Convolutional neural networks (CNNs) show impressive performance for ima...
research
∙
09/26/2016
Optimistic and Pessimistic Neural Networks for Scene and Object Recognition
In this paper the application of uncertainty modeling to convolutional n...
research
∙
04/27/2016
Zero-shot object prediction using semantic scene knowledge
This work focuses on the semantic relations between scenes and objects f...
research
∙
04/01/2016