Melih Kandemir
Melih Kandemir
Associate Professor of Machine Learning at the University of Southern Denmark
Verified email at - Homepage
Cited by
Cited by
Evidential Deep Learning to Quantify Classification Uncertainty
M Sensoy, L Kaplan, M Kandemir
Advances in Neural Information Processing Systems (NeurIPS), 3179-3189, 2018
Automatic segmentation of colon glands using object-graphs
C Gunduz-Demir, M Kandemir, AB Tosun, C Sokmensuer
Medical image analysis 14 (1), 1-12, 2010
Computer-aided diagnosis from weak supervision: A benchmarking study
M Kandemir, FA Hamprecht
Computerized medical imaging and graphics 42, 44-50, 2015
An augmented reality interface to contextual information
A Ajanki, M Billinghurst, H Gamper, T Järvenpää, M Kandemir, S Kaski, ...
Virtual reality 15, 161-173, 2011
Object-oriented texture analysis for the unsupervised segmentation of biopsy images for cancer detection
AB Tosun, M Kandemir, C Sokmensuer, C Gunduz-Demir
Pattern Recognition 42 (6), 1104-1112, 2009
Empowering multiple instance histopathology cancer diagnosis by cell graphs
M Kandemir, C Zhang, FA Hamprecht
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014
Asymmetric Transfer Learning with Deep Gaussian Processes
M Kandemir
International Conference on Machine Learning, 730-738, 2015
Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals
JP Kauppi, M Kandemir, VM Saarinen, L Hirvenkari, L Parkkonen, A Klami, ...
NeuroImage 112, 288-298, 2015
Deep Active Learning with Adaptive Acquisition
M Haußmann, FA Hamprecht, M Kandemir
International Joint Conference on Artificial Intelligence (IJCAI), arXiv …, 2019
Multi-task and multi-view learning of user state
M Kandemir, A Vetek, M Gönen, A Klami, S Kaski
Neurocomputing 139, 97-106, 2014
Gaussian process density counting from weak supervision
M von Borstel, M Kandemir, P Schmidt, MK Rao, K Rajamani, ...
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
Digital pathology: Multiple instance learning can detect Barrett's cancer
M Kandemir, A Feuchtinger, A Walch, FA Hamprecht
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 1348-1351, 2014
Variational Bayesian Multiple Instance Learning with Gaussian Processes
M Haußmann, FA Hamprecht, M Kandemir
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
Sampling-Free Variational Inference of Bayesian Neural Nets with Variance Backpropagation
M Haussmann, FA Hamprecht, M Kandemir
Uncertainty in Artificial Intelligence (UAI), arXiv preprint arXiv:1805.07654, 2019
Inferring object relevance from gaze in dynamic scenes
M Kandemir, VM Saarinen, S Kaski
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications …, 2010
Instance Label Prediction by Dirichlet Process Multiple Instance Learning.
M Kandemir, FA Hamprecht
UAI, 380-389, 2014
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes
M Haussmann, S Gerwinn, A Look, B Rakitsch, M Kandemir
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Multiple instance learning: Robust validation on retinopathy of prematurity
P Rani, R Elagiri Ramalingam, KT Rajamani, M Kandemir, D Singh
Int J Ctrl Theory Appl 9, 451-459, 2016
Contextual information access with augmented reality
A Ajanki, M Billinghurst, T Järvenpää, M Kandemir, S Kaski, M Koskela, ...
2010 IEEE International Workshop on Machine Learning for Signal Processing …, 2010
Learning relevance from natural eye movements in pervasive interfaces
M Kandemir, S Kaski
Proceedings of the 14th ACM international conference on Multimodal …, 2012
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