What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Alexander C. Berg focuses on Artificial intelligence, Machine learning, Pattern recognition, Pascal and Contextual image classification.
As part of his studies on Artificial intelligence, Alexander C. Berg often connects relevant subjects like Natural language processing.
Video tracking is closely connected to The Internet in his research, which is encompassed under the umbrella topic of Machine learning.
In his study, Convolutional neural network and Algorithm is strongly linked to Image resolution, which falls under the umbrella field of Pascal.
His work on Contextual image classification is being expanded to include thematically relevant topics such as Object.
He has included themes like Categorical variable and Benchmark in his Object detection study.
His most cited work include:
- ImageNet Large Scale Visual Recognition Challenge (18266 citations)
- SSD: Single Shot MultiBox Detector (9301 citations)
- Attribute and simile classifiers for face verification (1125 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Computer vision, Machine learning, Pattern recognition and Object.
His biological study spans a wide range of topics, including Context and Natural language processing.
His work on Pixel as part of general Computer vision research is often related to Efficient energy use and Detector, thus linking different fields of science.
His studies in Machine learning integrate themes in fields like Contextual image classification, Question answering, Benchmark, Visualization and Pattern recognition.
In Contextual image classification, Alexander C. Berg works on issues like Cognitive neuroscience of visual object recognition, which are connected to Quadratic programming and Image processing.
He has researched Object in several fields, including Robot, Semantic hierarchy, Data mining and Categorization.
He most often published in these fields:
- Artificial intelligence (82.57%)
- Computer vision (33.94%)
- Machine learning (22.02%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (82.57%)
- Computer vision (33.94%)
- Object (19.27%)
In recent papers he was focusing on the following fields of study:
Alexander C. Berg mainly investigates Artificial intelligence, Computer vision, Object, Object detection and Detector.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Pattern recognition.
His work on Active learning as part of general Machine learning study is frequently linked to Active learning, therefore connecting diverse disciplines of science.
His Pattern recognition research focuses on subjects like Projection, which are linked to Parsing.
His Object research includes elements of RGB color model and Active vision.
His research integrates issues of Correlation and Benchmark in his study of Visualization.
Between 2016 and 2021, his most popular works were:
- DSSD : Deconvolutional Single Shot Detector. (759 citations)
- Transformation-Grounded Image Generation Network for Novel 3D View Synthesis (179 citations)
- A dataset for developing and benchmarking active vision (98 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, Object and Detector.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Transformation and Reduction.
His Pixel and Image study in the realm of Computer vision interacts with subjects such as BitTorrent tracker and Online adaptation.
The Object detection study combines topics in areas such as RGB color model, Robotics, Active vision and Reinforcement learning.
The study incorporates disciplines such as Robot, Viola–Jones object detection framework, Convolutional neural network and Object model in addition to RGB color model.
Alexander C. Berg integrates many fields in his works, including Object, Focus and Benchmarking.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
