2023 - Research.com Best Female Scientist Award
2023 - Research.com Computer Science in United States Leader Award
2022 - Research.com Best Female Scientist Award
His study connects Categorization and Artificial intelligence. His research on Pattern recognition (psychology) often connects related areas such as Object detection. Li Fei-Fei regularly links together related areas like Pattern recognition (psychology) in his Object detection studies. Computer vision and Machine learning are two areas of study in which he engages in interdisciplinary work. He incorporates Machine learning and Computer vision in his studies. His Object (grammar) study frequently intersects with other fields, such as Cognitive neuroscience of visual object recognition. Cognitive neuroscience of visual object recognition is closely attributed to Object (grammar) in his work. His Image (mathematics) study frequently links to adjacent areas such as Contextual image classification. He frequently studies issues relating to Image (mathematics) and Contextual image classification.
His Artificial intelligence research covers fields of interest such as Machine learning, Computer vision, Natural language processing, Artificial neural network, Cognitive psychology and Human–computer interaction. Machine learning and Artificial intelligence are two areas of study in which he engages in interdisciplinary work. His research on Programming language frequently connects to adjacent areas such as Set (abstract data type). Set (abstract data type) is closely attributed to Programming language in his study. His Task (project management) study frequently draws parallels with other fields, such as Management. His research on Management often connects related areas such as Task (project management). By researching both Neuroscience and Perception, he produces research that crosses academic boundaries. Li Fei-Fei integrates many fields, such as Perception and Neuroscience, in his works. In his works, he conducts interdisciplinary research on Law and Politics.
Li Fei-Fei conducts interdisciplinary study in the fields of Artificial intelligence and Deep learning through his works. In his papers, Li Fei-Fei integrates diverse fields, such as Human–computer interaction and Operating system. He integrates many fields in his works, including Operating system and Human–computer interaction. Li Fei-Fei regularly links together related areas like Segmentation in his Computer vision studies. As part of his studies on Segmentation, he often connects relevant subjects like Computer vision. In his papers, he integrates diverse fields, such as Machine learning and Artificial intelligence. Li Fei-Fei undertakes multidisciplinary studies into Neuroscience and Developmental psychology in his work. He integrates many fields in his works, including Developmental psychology and Neuroscience. His study brings together the fields of Movement disorders and Pathology.
His Law study frequently intersects with other fields, such as Health care and Foundation (evidence). As part of his studies on Health care, he often connects relevant subjects like Law. He is involved in relevant fields of research such as Software deployment and Process (computing) in the domain of Operating system. He merges many fields, such as Process (computing) and Operating system, in his writings. In his articles, Li Fei-Fei combines various disciplines, including Artificial intelligence and Data science. Li Fei-Fei conducted interdisciplinary study in his works that combined Data science and Artificial intelligence. Li Fei-Fei conducts interdisciplinary study in the fields of Human–computer interaction and Computer vision through his research. He integrates Computer vision and Multimodal interaction in his research. Li Fei-Fei integrates many fields in his works, including Multimodal interaction and Human–computer interaction.
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ImageNet: A large-scale hierarchical image database
Jia Deng;Wei Dong;Richard Socher;Li-Jia Li.
computer vision and pattern recognition (2009)
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky;Jia Deng;Hao Su;Jonathan Krause.
International Journal of Computer Vision (2015)
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Justin Johnson;Alexandre Alahi;Li Fei-Fei.
european conference on computer vision (2016)
Large-Scale Video Classification with Convolutional Neural Networks
Andrej Karpathy;George Toderici;Sanketh Shetty;Thomas Leung.
computer vision and pattern recognition (2014)
A Bayesian hierarchical model for learning natural scene categories
L. Fei-Fei;P. Perona.
computer vision and pattern recognition (2005)
Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories
Li Fei-Fei;R. Fergus;P. Perona.
computer vision and pattern recognition (2004)
Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories
Li Fei-Fei;Rob Fergus;Pietro Perona.
Computer Vision and Image Understanding (2007)
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy;Li Fei-Fei.
computer vision and pattern recognition (2015)
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy;Li Fei-Fei.
computer vision and pattern recognition (2015)
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Ranjay Krishna;Yuke Zhu;Oliver Groth;Justin Johnson.
International Journal of Computer Vision (2017)
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