Search Results for author: Marcel Simon

Found 9 papers, 3 papers with code

Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring Algorithms in Whole Slide Images of Breast Cancer Tissues

no code implementations23 May 2017 Talha Qaiser, Abhik Mukherjee, Chaitanya Reddy Pb, Sai Dileep Munugoti, Vamsi Tallam, Tomi Pitkäaho, Taina Lehtimäki, Thomas Naughton, Matt Berseth, Aníbal Pedraza, Ramakrishnan Mukundan, Matthew Smith, Abhir Bhalerao, Erik Rodner, Marcel Simon, Joachim Denzler, Chao-Hui Huang, Gloria Bueno, David Snead, Ian Ellis, Mohammad Ilyas, Nasir Rajpoot

In this paper, we report on a recent automated Her2 scoring contest, held in conjunction with the annual PathSoc meeting held in Nottingham in June 2016, aimed at systematically comparing and advancing the state-of-the-art Artificial Intelligence (AI) based automated methods for Her2 scoring.

whole slide images

Generalized orderless pooling performs implicit salient matching

2 code implementations ICCV 2017 Marcel Simon, Yang Gao, Trevor Darrell, Joachim Denzler, Erik Rodner

In this paper, we generalize average and bilinear pooling to "alpha-pooling", allowing for learning the pooling strategy during training.

ImageNet pre-trained models with batch normalization

3 code implementations5 Dec 2016 Marcel Simon, Erik Rodner, Joachim Denzler

Convolutional neural networks (CNN) pre-trained on ImageNet are the backbone of most state-of-the-art approaches.

Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches

no code implementations21 Oct 2016 Erik Rodner, Marcel Simon, Robert B. Fisher, Joachim Denzler

In this paper, we study the sensitivity of CNN outputs with respect to image transformations and noise in the area of fine-grained recognition.

Neither Quick Nor Proper -- Evaluation of QuickProp for Learning Deep Neural Networks

no code implementations14 Jun 2016 Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler

Neural networks and especially convolutional neural networks are of great interest in current computer vision research.

Semantic Segmentation

Fine-grained Recognition Datasets for Biodiversity Analysis

no code implementations3 Jul 2015 Erik Rodner, Marcel Simon, Gunnar Brehm, Stephanie Pietsch, J. Wolfgang Wägele, Joachim Denzler

In the following paper, we present and discuss challenging applications for fine-grained visual classification (FGVC): biodiversity and species analysis.

Classification Fine-Grained Image Classification +1

Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks

no code implementations ICCV 2015 Marcel Simon, Erik Rodner

Part models of object categories are essential for challenging recognition tasks, where differences in categories are subtle and only reflected in appearances of small parts of the object.

Data Augmentation Model Discovery

Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding

no code implementations23 Feb 2015 Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler

Classifying single image patches is important in many different applications, such as road detection or scene understanding.

Scene Understanding

Part Detector Discovery in Deep Convolutional Neural Networks

1 code implementation12 Nov 2014 Marcel Simon, Erik Rodner, Joachim Denzler

Current fine-grained classification approaches often rely on a robust localization of object parts to extract localized feature representations suitable for discrimination.

General Classification

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