What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Face and Segmentation.
His Artificial intelligence research integrates issues from Machine learning, Regression and Code.
His study in the field of Tracking system is also linked to topics like Initialization.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Margin, Kadir–Brady saliency detector, Image and Boundary.
His work on Face detection as part of general Face research is frequently linked to Set and Cascade, bridging the gap between disciplines.
His Segmentation research includes elements of Convolutional neural network and Pooling.
His most cited work include:
- Deformable Convolutional Networks (1352 citations)
- Saliency Optimization from Robust Background Detection (949 citations)
- Face Alignment by Explicit Shape Regression (757 citations)
What are the main themes of his work throughout his whole career to date?
Yichen Wei focuses on Artificial intelligence, Computer vision, Pattern recognition, Object detection and Pose.
Yichen Wei frequently studies issues relating to Machine learning and Artificial intelligence.
His Pattern recognition research incorporates elements of Margin, Image, Object Class and Heuristic.
His study on Object detection also encompasses disciplines like
- Pooling that connect with fields like Convolutional neural network,
- Code that intertwine with fields like Motion blur.
His 3D pose estimation study, which is part of a larger body of work in Pose, is frequently linked to Task, bridging the gap between disciplines.
His study in the fields of Face detection under the domain of Face overlaps with other disciplines such as Set.
He most often published in these fields:
- Artificial intelligence (84.62%)
- Computer vision (48.35%)
- Pattern recognition (30.77%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (84.62%)
- Object detection (21.98%)
- Computer vision (48.35%)
In recent papers he was focusing on the following fields of study:
Yichen Wei mostly deals with Artificial intelligence, Object detection, Computer vision, Pose and Pattern recognition.
His work on Code expands to the thematically related Artificial intelligence.
His studies in Object detection integrate themes in fields like Motion, Pooling and Detector.
His work on Feature as part of general Computer vision study is frequently connected to Graph, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His research in Pose focuses on subjects like Machine learning, which are connected to Tracking and Simple.
The study incorporates disciplines such as Texture, Similarity and Re identification in addition to Pattern recognition.
Between 2016 and 2021, his most popular works were:
- Deformable Convolutional Networks (1352 citations)
- Simple Baselines for Human Pose Estimation and Tracking (540 citations)
- Relation Networks for Object Detection (497 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of study are Artificial intelligence, Computer vision, Object detection, Code and Pose.
Artificial intelligence is often connected to Machine learning in his work.
His Machine learning study incorporates themes from Tracking and Simple.
His Pose study combines topics in areas such as Regression analysis, Representation and Data mining.
Yichen Wei works mostly in the field of Feature extraction, limiting it down to topics relating to Feature and, in certain cases, Object and Cognitive neuroscience of visual object recognition.
His biological study spans a wide range of topics, including Pooling and Convolutional neural network.
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