What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Computer vision
Cong Yao spends much of his time researching Artificial intelligence, Pattern recognition, Artificial neural network, Feature extraction and Computer vision.
His work in the fields of Artificial intelligence, such as Representation, Orientation and Pattern recognition, overlaps with other areas such as Variable and Emphasis.
His work on Segmentation as part of general Pattern recognition study is frequently linked to Scale, bridging the gap between disciplines.
His Segmentation research incorporates themes from End-to-end principle, Deep learning and Spotting.
His Feature extraction study incorporates themes from Pipeline, Word, Data mining and Resolution.
His Intelligent character recognition study combines topics in areas such as Text mining, Speech recognition, Convolutional neural network and Lexicon.
His most cited work include:
- An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition (966 citations)
- EAST: An Efficient and Accurate Scene Text Detector (547 citations)
- Detecting texts of arbitrary orientations in natural images (537 citations)
What are the main themes of his work throughout his whole career to date?
Cong Yao focuses on Artificial intelligence, Pattern recognition, Computer vision, Segmentation and Image.
His work on Machine learning expands to the thematically related Artificial intelligence.
The Feature extraction research Cong Yao does as part of his general Pattern recognition study is frequently linked to other disciplines of science, such as Rectification, therefore creating a link between diverse domains of science.
His Feature extraction study integrates concerns from other disciplines, such as Normalization and Lexicon.
His Computer vision research includes themes of Character and Perspective.
Cong Yao interconnects Noise and Convolutional neural network in the investigation of issues within Segmentation.
He most often published in these fields:
- Artificial intelligence (84.62%)
- Pattern recognition (51.92%)
- Computer vision (25.96%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (84.62%)
- Pattern recognition (51.92%)
- Differentiable function (4.81%)
In recent papers he was focusing on the following fields of study:
Cong Yao mostly deals with Artificial intelligence, Pattern recognition, Differentiable function, Computer vision and Key.
His study in the field of Perspective, Text detection and Deep learning is also linked to topics like Context model.
Cong Yao is involved in the study of Pattern recognition that focuses on Segmentation in particular.
His Segmentation research includes elements of Artificial neural network, Spotting, End-to-end principle and Benchmark.
His work on Rendering and Real image as part of general Computer vision research is frequently linked to 3D computer graphics and Metaverse, bridging the gap between disciplines.
His work investigates the relationship between Key and topics such as Object detection that intersect with problems in Feature.
Between 2019 and 2021, his most popular works were:
- Real-Time Scene Text Detection with Differentiable Binarization (44 citations)
- Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes (44 citations)
- Scene Text Detection and Recognition: The Deep Learning Era (14 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
Artificial intelligence, Pattern recognition, Segmentation, Deep learning and Benchmark are his primary areas of study.
His Artificial intelligence research is mostly focused on the topic Text detection.
His study in Text detection is interdisciplinary in nature, drawing from both Perspective and Training set.
He has included themes like Synthetic data and Mindset in his Deep learning study.
Throughout his Process studies, Cong Yao incorporates elements of other sciences such as Differentiable function, Code, Set and Detector.
His Task analysis investigation overlaps with Pipeline, Representation, Artificial neural network, End-to-end principle and Spotting.
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