333 citations · 1.1k across the 20 of their papers we have counts for
22 papers
Evaluating Zero-cost Active Learning for Object Detection
Dominik Probst, Hasnain Raza, Erik Rodner
Object detection requires substantial labeling effort for learning robust models. Active learning can reduce this effort by intelligently selecting relevant examples to be annotate…
Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentation
Simon Reiß, Constantin Seibold, Alexander Freytag +2
Pixel-wise segmentation is one of the most data and annotation hungry tasks in our field. Providing representative and accurate annotations is often mission-critical especially for…
Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection
Björn Barz, Erik Rodner, Yanira Guanche Garcia +1
Automatic detection of anomalies in space- and time-varying measurements is an important tool in several fields, e.g., fraud detection, climate analysis, or healthcare monitoring.…
Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring Algorithms in Whole Slide Images of Breast Cancer Tissues
Talha Qaiser, Abhik Mukherjee, Chaitanya Reddy Pb +19
Evaluating expression of the Human epidermal growth factor receptor 2 (Her2) by visual examination of immunohistochemistry (IHC) on invasive breast cancer (BCa) is a key part of th…
Generalized orderless pooling performs implicit salient matching
Marcel Simon, Yang Gao, Trevor Darrell +2
Most recent CNN architectures use average pooling as a final feature encoding step. In the field of fine-grained recognition, however, recent global representations like bilinear p…
Fast Learning and Prediction for Object Detection using Whitened CNN Features
Björn Barz, Erik Rodner, Christoph Käding +1
We combine features extracted from pre-trained convolutional neural networks (CNNs) with the fast, linear Exemplar-LDA classifier to get the advantages of both: the high detection…