Igel, B.[Burkhard]
* 2008: Adaptive speech enhancement with varying noise backgrounds
* 2009: Distributed Audio Network for Speech Enhancement in Challenging Noise Backgrounds
Igel, C.[Christian]
* 2010: Efficient update of the covariance matrix inverse in iterated linear discriminant analysis
* 2010: Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets
* 2010: Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
* 2011: Improved Working Set Selection for LaRank
* 2012: Introduction to Restricted Boltzmann Machines, An
* 2012: Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition
* 2013: Linear feature selection in texture analysis: A PLS based method
* 2013: Shape Index Descriptors Applied to Texture-Based Galaxy Analysis
* 2014: Training restricted Boltzmann machines: An introduction
* 2016: Integrated Optimization of Long-Range Underwater Signal Detection, Feature Extraction, and Classification for Nuclear Treaty Monitoring
* 2016: Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring
* 2017: Adaptive pattern recognition in real-time video-based soccer analysis
* 2017: Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy
* 2018: Population-Contrastive-Divergence: Does consistency help with RBM training?
* 2020: Label-similarity Curriculum Learning
* 2022: Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods
Includes: Igel, C.[Christian] Igel, C.
16 for Igel, C.
Igel, J.
* 2014: Influence of Heterogeneous Soils and Clutter on the Performance of Ground-Penetrating Radar for Landmine Detection
Igelmo, M.[Manuel]
* 2010: Conductance Electrical Model for Representing and Matching Weighted Undirected Graphs, A
* 2012: Compact Form of the Pseudo-Inverse Matrix in the Approximation of a Star Graph Using the Conductance Electrical Model (CEM)
* 2016: Filtering graphs to check isomorphism and extracting mapping by using the Conductance Electrical Model