Kevin Smith

Affiliations:
  • KTH Royal Institute of Technology, Sweden
  • University of Basel, Switzerland (former)
  • EPFL, Lausanne, Switzerland (former)


According to our database1, Kevin Smith authored at least 29 papers between 2004 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Bridging Generalization Gaps in High Content Imaging Through Online Self-Supervised Domain Adaptation.
CoRR, 2023

Are Natural Domain Foundation Models Useful for Medical Image Classification?
CoRR, 2023

Pretrained ViTs Yield Versatile Representations For Medical Images.
CoRR, 2023

PatchDropout: Economizing Vision Transformers Using Patch Dropout.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Metadata-guided Consistency Learning for High Content Images.
Proceedings of the Medical Imaging with Deep Learning, 2023

2022
The potential of artificial intelligence for achieving healthy and sustainable societies.
CoRR, 2022

What Makes Transfer Learning Work for Medical Images: Feature Reuse & Other Factors.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Is it Time to Replace CNNs with Transformers for Medical Images?
CoRR, 2021

CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020
Decoupling Inherent Risk and Early Cancer Signs in Image-Based Breast Cancer Risk Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Adding seemingly uninformative labels helps in low data regimes.
Proceedings of the 37th International Conference on Machine Learning, 2020

Explanation-Based Weakly-Supervised Learning of Visual Relations with Graph Networks.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
An Empirical Study of the Relation Between Network Architecture and Complexity.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
The Preimage of Rectifier Network Activities.
Proceedings of the 5th International Conference on Learning Representations, 2017

2015
Learning Structured Models for Segmentation of 2-D and 3-D Imagery.
IEEE Trans. Medical Imaging, 2015

2012
Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks With Learned Shape Features.
IEEE Trans. Medical Imaging, 2012

SLIC Superpixels Compared to State-of-the-Art Superpixel Methods.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Structured Image Segmentation Using Kernelized Features.
Proceedings of the Computer Vision - ECCV 2012, 2012

2011
Are spatial and global constraints really necessary for segmentation?
Proceedings of the IEEE International Conference on Computer Vision, 2011

2010
A Fully Automated Approach to Segmentation of Irregularly Shaped Cellular Structures in EM Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

2008
Tracking the Visual Focus of Attention for a Varying Number of Wandering People.
IEEE Trans. Pattern Anal. Mach. Intell., 2008

2006
Multi-person Tracking in Meetings: A Comparative Study.
Proceedings of the Machine Learning for Multimodal Interaction, 2006


Tracking the multi person wandering visual focus of attention.
Proceedings of the 8th International Conference on Multimodal Interfaces, 2006

2D Multi-person Tracking: A Comparative Study in AMI Meetings.
Proceedings of the Multimodal Technologies for Perception of Humans, 2006

2005
Evaluating Multi-Object Tracking.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005

Using Particles to Track Varying Numbers of Interacting People.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

2004
Order Matters: A Distributed Sampling Method for Multi-Object Tracking.
Proceedings of the British Machine Vision Conference, 2004


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