Iba pa

Machine Vision for Cultural Heritage & Natural Science Collections

Name: Machine Vision for Cultural Heritage & Natural Science Collections
Genre: Iba pa
Released: 2019-12-02
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20193h 15m★ 0

Iba pa

The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. The Yale-Smithsonian Partnership brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships.

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Mga Komento

10 Mga Komento

Belle_by92🌺🌹❤️Nov 24, 2025

Susan Gibbons (University Librarian & Deputy Provost, Yale) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. dhlab.yal

KobbyNov 24, 2025

Jacob Kim (Hirshhorn, Smithsonian Institution) & Dan Michaelson (School of Art, Yale) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and futu

RosaNov 24, 2025

Stephen Krewson (English, Yale) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. dhlab.yale.edu/machine-vision

Yaka mwanaNov 24, 2025

Adam Metallo (Digitization Program Office, Smithsonian Institution) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. d

Sarah ElizabethNov 24, 2025

Catherine DeRose (DHLab, Yale) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. dhlab.yale.edu/machine-vision

ScuderiaNov 24, 2025

Alex White (NMNH & Data Science Lab, Smithsonian Institution) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. dhlab.y

AhmedFathyActorNov 24, 2025

Douglas Duhaime (DHLab, Yale) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. dhlab.yale.edu/machine-vision

Donald KarisebNov 24, 2025

Peter Leonard (DHLab, Yale) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. dhlab.yale.edu/machine-vision

Depi😍😍Nov 24, 2025

Holly Rushmeier (Computer Science, Yale) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. dhlab.yale.edu/machine-visio

BlaqBonezNov 24, 2025

Rebecca Dikow (Data Science Lab, Smithsonian Institution) The Yale-Smithsonian Partnership presents: Machine Vision for Cultural Heritage & Natural Science Collections The mass digitization of visual collections, on the order of hundreds of thousands or millions of images, creates new challenges for curators and researchers alike. Simultaneously, the rapid pace of industry innovation in deep learning (from guiding self-driving cars to captioning smartphone images) demands the attention of library, museum, and academic professionals. Existing practices of cataloging and description can be augmented by recent advancements in machine vision – and human expertise can likewise guide the development of future algorithms for the humanities and sciences alike. This event, held at the Franke Family Digital Humanities Laboratory in Yale’s Sterling Memorial Library, brings together scholars and curators from both institutions for conversations, demonstrations, and future partnerships. dhlab.yale.

Machine Vision for Cultural Heritage & Natural Science Collections

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