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Daniel Huber
Researcher at University of Geneva
Publications - 145
Citations - 18055
Daniel Huber is an academic researcher from University of Geneva. The author has contributed to research in topics: Point cloud & Laser scanning. The author has an hindex of 56, co-authored 144 publications receiving 16117 citations. Previous affiliations of Daniel Huber include Howard Hughes Medical Institute & Stanford University.
Papers
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Journal ArticleDOI
Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators
Lin Tian,S. Andrew Hires,Tianyi Mao,Daniel Huber,M. Eugenia Chiappe,Sreekanth H. Chalasani,Leopoldo Petreanu,Jasper Akerboom,Sean A McKinney,Sean A McKinney,Eric R. Schreiter,Cornelia I. Bargmann,Vivek Jayaraman,Karel Svoboda,Loren L. Looger +14 more
TL;DR: A single-wavelength GCaMP2-based GECI (GCaMP3) is developed, with increased baseline fluorescence, increased dynamic range and higher affinity for calcium, and long-term imaging in the motor cortex of behaving mice revealed large fluorescence changes in imaged neurons over months.
Book ChapterDOI
Recognizing Objects in Range Data Using Regional Point Descriptors
TL;DR: Two new regional shape descriptors are introduced: 3D shape contexts and harmonic shape contexts that outperform the others on cluttered scenes on recognition of vehicles in range scans of scenes using a database of 56 cars.
Journal ArticleDOI
Channelrhodopsin-2-assisted circuit mapping of long-range callosal projections
Leopoldo Petreanu,Daniel Huber,Daniel Huber,Aleksander Sobczyk,Aleksander Sobczyk,Karel Svoboda,Karel Svoboda +6 more
TL;DR: It is shown that the light-gated channel channelrhodopsin-2 (ChR2) is delivered to axons in pyramidal neurons in vivo, and laminar specificity may be identical for local and long-range cortical projections.
Journal ArticleDOI
Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques
TL;DR: This article surveys techniques developed in civil engineering and computer science that can be utilized to automate the process of creating as-built BIMs and outlines the main methods used by these algorithms for representing knowledge about shape, identity, and relationships.
Journal ArticleDOI
Vasopressin and oxytocin excite distinct neuronal populations in the central amygdala.
TL;DR: This work identified two neuronal populations in the central amygdala as part of an inhibitory network, through which vasopressin and oxytocin modulate the integration of excitatory information from the basolateral amygdala and cerebral cortex in opposite manners.