Yahoo Search Búsqueda en la Web

Resultado de búsqueda

  1. Hace 3 días · Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute. She served as the Director of Stanford’s AI Lab from 2013 to 2018.

  2. Hace 2 días · Fei-Fei Li: Conocida por su trabajo en visión por computadora y aprendizaje profundo, ha liderado proyectos cruciales como ImageNet, que ha impulsado significativamente el desarrollo de la IA en reconocimiento de imágenes.

  3. research.samsung.com › blog › LearningBLOG | Samsung Research

    Hace 15 horas · [11] Yuke Zhu, Joseph J Lim, and Li Fei-Fei, “Knowledge acquisition for visual question answering via iterative querying,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 1154–1163.

  4. Hace 15 horas · Keeping this in view, in 2009, Prof. Fei-Fei Lee (of Stanford University) In 2009, Fei-Fei Li created ImageNet, which became the largest database of its kind with more than 14 million URLs of images, almost all of which were hand-labeled (or annotated) to indicate as to what they contained [5].

  5. Hace 2 días · For example, one of True's former students, Fei-Fei Li, is now a professor at Stanford University and the director of the Stanford Artificial Intelligence Lab. Li is a leading expert in computer vision, and her work has had a major impact on the development of self-driving cars and other AI-powered technologies.

  6. Hace 4 días · Liu et al. (2024) Haotian Liu, Chunyuan Li, Yuheng Li, and Yong Jae Lee. 2024. Improved Baselines with Visual Instruction Tuning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 26296–26306. Liu et al. (2023) Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2023. Visual Instruction Tuning.

  7. Hace 4 días · DOI: 10.1038/s41598-024-66346-w Corpus ID: 270970865; Going beyond still images to improve input variance resilience in multi-stream vision understanding models @article{Fadaei2024GoingBS, title={Going beyond still images to improve input variance resilience in multi-stream vision understanding models}, author={AmirHosein Fadaei and Mohammad-Reza Abolghasemi Dehaqani}, journal={Scientific ...