What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His primary scientific interests are in Artificial intelligence, Pattern recognition, Computer vision, Object detection and Convolutional neural network.
His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Machine learning.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Feature, Contextual image classification, Facial recognition system, Histogram and Kadir–Brady saliency detector.
The study incorporates disciplines such as Frame rate and Viola–Jones object detection framework in addition to Object detection.
His Convolutional neural network research incorporates elements of Deep learning and Speedup.
Jian Sun has researched Artificial neural network in several fields, including Residual and Test set.
His most cited work include:
- Deep Residual Learning for Image Recognition (61800 citations)
- Faster R-CNN: towards real-time object detection with region proposal networks (12666 citations)
- Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification (7908 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Image and Object detection.
His research ties Machine learning and Artificial intelligence together.
Jian Sun has included themes like Facial recognition system and Feature in his Pattern recognition study.
His research combines Computer graphics and Computer vision.
Jian Sun combines subjects such as Algorithm, Detector, Task and Code with his study of Object detection.
As a part of the same scientific study, he usually deals with the Convolutional neural network, concentrating on Deep learning and frequently concerns with Artificial neural network.
He most often published in these fields:
- Artificial intelligence (71.96%)
- Pattern recognition (35.28%)
- Computer vision (34.11%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (71.96%)
- Pattern recognition (35.28%)
- Object detection (15.19%)
In recent papers he was focusing on the following fields of study:
Jian Sun focuses on Artificial intelligence, Pattern recognition, Object detection, Code and Segmentation.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Point, Machine learning and Computer vision.
His work carried out in the field of Computer vision brings together such families of science as Iterative method and Constraint.
Jian Sun interconnects Embedding, Graph, Feature and Graph in the investigation of issues within Pattern recognition.
His study in Object detection is interdisciplinary in nature, drawing from both Contextual image classification, Algorithm and Detector.
His work on Residual neural network as part of his general Artificial neural network study is frequently connected to Meta learning, thereby bridging the divide between different branches of science.
Between 2018 and 2021, his most popular works were:
- Single Path One-Shot Neural Architecture Search with Uniform Sampling (169 citations)
- DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation (113 citations)
- MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning (98 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Object detection, Discriminative model and Detector.
His Artificial intelligence study frequently links to adjacent areas such as Machine learning.
His research in Pattern recognition intersects with topics in Contextual image classification, Pixel, Spatial analysis and Generative grammar.
His Contextual image classification research focuses on subjects like Task, which are linked to Computer vision and Point.
His Object detection study introduces a deeper knowledge of Object.
His biological study deals with issues like Pascal, which deal with fields such as Computer hardware and Differentiable function.
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