2022 - Research.com Best Female Scientist Award
Li Fei-Fei mainly investigates Artificial intelligence, Machine learning, Pattern recognition, Object and Computer vision. Her research in Cognitive neuroscience of visual object recognition, Visualization, Categorization, Contextual image classification and Feature extraction are components of Artificial intelligence. Her Cognitive neuroscience of visual object recognition research also works with subjects such as
Her Contextual image classification research is multidisciplinary, relying on both Graphical model, WordNet, Information retrieval and Image retrieval. Her research in Machine learning intersects with topics in Probabilistic logic and Caltech 101. Her Pattern recognition research integrates issues from Pixel and Image.
Li Fei-Fei mainly focuses on Artificial intelligence, Machine learning, Pattern recognition, Computer vision and Object. Her work on Artificial intelligence is being expanded to include thematically relevant topics such as Natural language processing. Her work carried out in the field of Machine learning brings together such families of science as Contextual image classification, Robot, Training set and Data mining.
Her Robot study combines topics in areas such as Representation, Task and Set. Her Pattern recognition research incorporates elements of Image and Feature. Li Fei-Fei has researched Object in several fields, including Representation and Human–computer interaction.
Her scientific interests lie mostly in Artificial intelligence, Robot, Human–computer interaction, Machine learning and Reinforcement learning. The study incorporates disciplines such as Computer vision and Pattern recognition in addition to Artificial intelligence. Her Pattern recognition research includes themes of Contextual image classification, Object detection and Categorization.
Her Robot research integrates issues from Leverage, Object, Task analysis, Robotic arm and RGB color model. Li Fei-Fei interconnects Question answering, Variety, Quality and Heuristics in the investigation of issues within Machine learning. Her studies in Benchmark integrate themes in fields like Path, Cognitive neuroscience of visual object recognition and Visual perception, Perception.
Li Fei-Fei spends much of her time researching Artificial intelligence, Robot, Visualization, Task analysis and Machine learning. Her Artificial intelligence study combines topics from a wide range of disciplines, such as Path and Pattern recognition. Her studies deal with areas such as Contextual image classification and Object detection as well as Pattern recognition.
Li Fei-Fei focuses mostly in the field of Object detection, narrowing it down to matters related to Cognitive neuroscience of visual object recognition and, in some cases, Benchmark. In her research, Feature learning, Vocabulary, WordNet and Ontology is intimately related to Representation, which falls under the overarching field of Visualization. Li Fei-Fei has included themes like Crowdsourcing, Robotics, Reinforcement and Heuristics in her Machine learning study.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
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)
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;Rob Fergus;Pietro Perona.
computer vision and pattern recognition (2004)
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Justin Johnson;Alexandre Alahi;Li Fei-Fei.
european conference on computer vision (2016)
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy;Li Fei-Fei.
computer vision and pattern recognition (2015)
Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
Juan Carlos Niebles;Hongcheng Wang;Li Fei-Fei.
International Journal of Computer Vision (2008)
One-shot learning of object categories
Li Fei-Fei;R. Fergus;P. Perona.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)
Large-scale Video Classification with Convolutional Neural Networks
Andrej Karpathy;George Toderici;Sanketh Shetty;Thomas Leung.
(2014)
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