What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Alexei A. Efros mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Image.
His work in Segmentation, Discriminative model, Object detection, Translation and Image translation is related to Artificial intelligence.
He works mostly in the field of Translation, limiting it down to topics relating to Graphics and, in certain cases, Domain.
His Pattern recognition research includes elements of Object and Contextual image classification.
The Machine learning study combines topics in areas such as Adversarial system and Face.
His work on Visual Word as part of general Image research is frequently linked to Set, bridging the gap between disciplines.
His most cited work include:
- Image-to-Image Translation with Conditional Adversarial Networks (7234 citations)
- Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks (6660 citations)
- Texture synthesis by non-parametric sampling (2454 citations)
What are the main themes of his work throughout his whole career to date?
Alexei A. Efros mainly focuses on Artificial intelligence, Computer vision, Image, Pattern recognition and Machine learning.
His Object, Segmentation, Pixel, Object detection and Convolutional neural network investigations are all subjects of Artificial intelligence research.
His work on Image segmentation, Image texture and Image processing as part of general Computer vision research is often related to Pipeline and Set, thus linking different fields of science.
His research integrates issues of Translation and Representation in his study of Image.
In the subject of general Pattern recognition, his work in Feature learning is often linked to Consistency, thereby combining diverse domains of study.
In his study, Pascal is inextricably linked to Training set, which falls within the broad field of Machine learning.
He most often published in these fields:
- Artificial intelligence (82.59%)
- Computer vision (43.30%)
- Image (24.55%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (82.59%)
- Computer vision (43.30%)
- Image (24.55%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Image, Pattern recognition and Range.
His work on Artificial intelligence is being expanded to include thematically relevant topics such as Machine learning.
Alexei A. Efros combines subjects such as Contextual image classification and Robustness with his study of Machine learning.
His work on Image translation as part of general Image study is frequently connected to Detector, Generator and Scripting language, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Image translation research is multidisciplinary, incorporating elements of Mutual information and Feature vector.
His work deals with themes such as Optical flow and Code, which intersect with Pattern recognition.
Between 2018 and 2021, his most popular works were:
- Everybody Dance Now (239 citations)
- Learning Correspondence From the Cycle-Consistency of Time (157 citations)
- CNN-Generated Images Are Surprisingly Easy to Spot… for Now (80 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
His primary scientific interests are in Artificial intelligence, Image, Pattern recognition, Machine learning and Translation.
His study in Segmentation, Feature learning, Deep learning, Face and Object is carried out as part of his Artificial intelligence studies.
His biological study spans a wide range of topics, including Computer graphics and Image warping.
The various areas that Alexei A. Efros examines in his Pattern recognition study include Autoencoder, Key and Code.
The concepts of his Machine learning study are interwoven with issues in Contextual image classification and Robustness.
His Computer vision research extends to the thematically linked field of Translation.
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