The Visual Computing Group, led by Hanspeter Pfister, explores and provides visual analysis tools and methods to help scientists and researchers better process and understand large, multi-dimensional data sets in various domains such as neuroscience, genomics, systems biology, astronomy, and medicine.
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On the Capability of Neural Networks to Generalize to Unseen Category-Pose Combinations
arXiv preprint arXiv:2007.08032.
—- Graphics
- Vision
- Preprint
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Fast Mitochondria Detection for Connectomics
Medical Imaging with Deep Learning.
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The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
—- Connectomics
- Vision
- Preprint
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Automated Measurements of Key Morphological Features of Human Embryos for IVF
arXiv.
—- Vision
- Preprint
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SportsXR - Immersive Analytics in Sports
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—- InfoVis
- HCI
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@HarvardVCGExcellent work from our own @spandan_madan and @hpfister on the Capability of Neural Networks to Generalize to Unse… Humans easily recognize new objects in unseen poses, but can CNNs? Our new work with @hpfister , @fredodurand , and… @spandan_madan -
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@HarvardVCGRT @flekschas: I'm excited to present our work on interactive visual pattern search in #epigenomic data using deep representation learning… -
Harvard VCG
@HarvardVCGFantastic collaboration with @danielhaehn from @UMassBoston on Fast Mitochondria Detection for Connectomics. Check… SPOTLIGHT at #MIDL2023: Fast Mitochondria Detection for Connectomics! We release two new benchmark datasets and a s… @danielhaehn -
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@HarvardVCG🎉 We are honored to share that @hpfister has been elected to ACM SIGGRAPH Academy @siggraph for “diverse contributi… -
Harvard VCG
@HarvardVCGRT @flekschas: Wow! 🤩 We're honored that our paper on Visual Pattern Search in Sequential Data received the Best Paper Award at #EuroVis202…