What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Computer vision
Artificial intelligence, Computer vision, RGB color model, Pattern recognition and Object detection are his primary areas of study.
His work in the fields of Artificial intelligence, such as Semantics and Visualization, overlaps with other areas such as Robot kinematics, Cognitive map and Plan.
Saurabh Gupta has included themes like Optical flow, Modality and Transfer in his Semantics study.
His work deals with themes such as Object, Pixel and Convolutional neural network, which intersect with RGB color model.
Saurabh Gupta interconnects Embedding, 3d model, Feature and Task in the investigation of issues within Pixel.
His Pattern recognition study incorporates themes from Image resolution, Cognitive neuroscience of visual object recognition and Contextual image classification.
His most cited work include:
- Learning Rich Features from RGB-D Images for Object Detection and Segmentation (1089 citations)
- From captions to visual concepts and back (934 citations)
- Microsoft COCO Captions: Data Collection and Evaluation Server (765 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Human–computer interaction, RGB color model and Convolutional neural network.
His work in Artificial intelligence covers topics such as Pattern recognition which are related to areas like Cognitive neuroscience of visual object recognition.
As part of one scientific family, Saurabh Gupta deals mainly with the area of Computer vision, narrowing it down to issues related to the Structure, and often Representation.
His research in Human–computer interaction intersects with topics in Variety and Reinforcement learning.
His RGB color model research is multidisciplinary, incorporating elements of Modality and Training set.
His study explores the link between Object and topics such as Pixel that cross with problems in Task.
He most often published in these fields:
- Artificial intelligence (59.49%)
- Computer vision (26.58%)
- Human–computer interaction (24.05%)
What were the highlights of his more recent work (between 2018-2021)?
- Human–computer interaction (24.05%)
- Artificial intelligence (59.49%)
- Action (11.39%)
In recent papers he was focusing on the following fields of study:
Saurabh Gupta mainly investigates Human–computer interaction, Artificial intelligence, Action, Reinforcement learning and Code.
His Human–computer interaction research includes themes of Variety and Embodied cognition.
His research integrates issues of Autonomous agent and Affordance in his study of Variety.
His research in the fields of Robot overlaps with other disciplines such as Cognitive map.
In general Robot study, his work on Motion planning often relates to the realm of Optimal control and Architecture, thereby connecting several areas of interest.
His work in the fields of Computer vision, such as Object and Matching, intersects with other areas such as Class, Frame and Spacetime.
Between 2018 and 2021, his most popular works were:
- Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data (48 citations)
- Learning to Explore using Active Neural SLAM (41 citations)
- PyRobot: An Open-source Robotics Framework for Research and Benchmarking. (37 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Computer vision
Saurabh Gupta focuses on Artificial intelligence, Leverage, Robot, Variety and Imitation learning.
He focuses mostly in the field of Artificial intelligence, narrowing it down to topics relating to Machine learning and, in certain cases, Modular design.
His work carried out in the field of Leverage brings together such families of science as Visual navigation and Real-time computing.
The Robot study combines topics in areas such as Applications of artificial intelligence, Interface, Software engineering and Focus.
His Variety study often links to related topics such as Human–computer interaction.
Other disciplines of study, such as Perception, Physical system, Frame rate and A priori and a posteriori, are mixed together with his Optimal control studies.
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