What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Artificial intelligence, Computer vision, Object detection, Image processing and Video tracking are his primary areas of study.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Pattern recognition.
Many of his studies involve connections with topics such as Intelligent sensor and Computer vision.
His studies in Object detection integrate themes in fields like Motion estimation, Object-class detection, Information retrieval and Feature detection.
His study in the field of Digital image processing is also linked to topics like Set.
Carlo S. Regazzoni interconnects Kalman filter, Tracking system, Data compression and Image fusion in the investigation of issues within Video tracking.
His most cited work include:
- Synthesis of unequally spaced arrays by simulated annealing (290 citations)
- Spectrum sensing: A distributed approach for cognitive terminals (221 citations)
- Abnormal event detection in videos using generative adversarial nets (181 citations)
What are the main themes of his work throughout his whole career to date?
Carlo S. Regazzoni mainly investigates Artificial intelligence, Computer vision, Image processing, Pattern recognition and Object detection.
His study brings together the fields of Machine learning and Artificial intelligence.
His biological study spans a wide range of topics, including Kalman filter and Robustness.
The concepts of his Image processing study are interwoven with issues in Real-time computing and Pattern recognition.
His research in Pattern recognition intersects with topics in Particle filter and Cluster analysis.
His work in Object detection is not limited to one particular discipline; it also encompasses Object-class detection.
He most often published in these fields:
- Artificial intelligence (61.27%)
- Computer vision (38.29%)
- Image processing (15.10%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (61.27%)
- Computer vision (38.29%)
- Machine learning (10.72%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Computer vision, Machine learning, Probabilistic logic and Cognitive radio.
His Pattern recognition research extends to Artificial intelligence, which is thematically connected.
The Computer vision study combines topics in areas such as Kalman filter and Trajectory.
In his study, Bayesian network and Hidden Markov model is strongly linked to Crowds, which falls under the umbrella field of Machine learning.
Carlo S. Regazzoni has included themes like Intelligent decision support system, Autonomous agent and Computer security in his Probabilistic logic study.
His Cognitive radio research includes themes of Radio spectrum and Electronic engineering, Wideband.
Between 2014 and 2021, his most popular works were:
- Abnormal event detection in videos using generative adversarial nets (181 citations)
- The Evolution of First Person Vision Methods: A Survey (128 citations)
- Online Nonparametric Bayesian Activity Mining and Analysis From Surveillance Video (39 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Carlo S. Regazzoni mostly deals with Artificial intelligence, Computer vision, Probabilistic logic, Pattern recognition and Machine learning.
His study in Artificial intelligence focuses on Particle filter, Video tracking, Kalman filter, Cluster analysis and Anomaly detection.
His study in the field of Segmentation also crosses realms of First person.
His Probabilistic logic research integrates issues from Computer security, Algorithm and Trajectory.
His work deals with themes such as Sensor fusion, Eye tracking, Robustness and Kriging, which intersect with Pattern recognition.
His Machine learning research includes elements of Population ageing and Social connectedness.
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