What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His scientific interests lie mostly in Artificial intelligence, Computer vision, Pattern recognition, Activity recognition and Discriminative model.
His study connects Machine learning and Artificial intelligence.
His Computer vision study incorporates themes from Human–computer interaction and Pattern recognition.
His research in Pattern recognition intersects with topics in Histogram and Feature.
His studies deal with areas such as Event recognition, Video tracking, Probabilistic logic, Finite-state machine and Component as well as Activity recognition.
The study incorporates disciplines such as Covariance matrix and Re identification in addition to Discriminative model.
His most cited work include:
- Event detection and analysis from video streams (429 citations)
- Video-based event recognition: activity representation and probabilistic recognition methods (299 citations)
- Person Re-identification Using Spatial Covariance Regions of Human Body Parts (181 citations)
What are the main themes of his work throughout his whole career to date?
François Brémond mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Video tracking.
His works in Feature extraction, Discriminative model, Activity recognition, Motion and Object are all subjects of inquiry into Artificial intelligence.
Feature extraction is often connected to Pedestrian detection in his work.
Tracking, Object detection, Pixel, Tracking system and Motion detection are the subjects of his Computer vision studies.
His research in Pattern recognition focuses on subjects like Cluster analysis, which are connected to Data mining.
His Machine learning research includes themes of Task, Activities of daily living and Action.
He most often published in these fields:
- Artificial intelligence (67.89%)
- Computer vision (33.33%)
- Pattern recognition (24.16%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (67.89%)
- Machine learning (18.65%)
- Pattern recognition (24.16%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Pattern recognition, Feature extraction and Motion.
His Artificial intelligence study frequently draws connections between related disciplines such as Activities of daily living.
His Machine learning research is multidisciplinary, relying on both Classifier, Biometrics and Action.
His studies in Pattern recognition integrate themes in fields like Representation, Representation, Orientation, Optical flow and Robustness.
His Feature extraction study also includes
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Pedestrian detection which intersects with area such as Detector, Object detection, Computer vision and Milestone,
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Facial recognition system which intersects with area such as Cognitive psychology, Motion analysis and Contextual image classification,
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Video tracking most often made with reference to Transfer of learning.
His Motion research also works with subjects such as
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Generative model that connect with fields like Decomposition,
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Task, which have a strong connection to Rating scale and Gerontology.
Between 2017 and 2021, his most popular works were:
- Is it time to revise the diagnostic criteria for apathy in brain disorders? The 2018 international consensus group. (63 citations)
- Mitigating Bias in Gender, Age and Ethnicity Classification: a Multi-Task Convolution Neural Network Approach (47 citations)
- Skeleton Image Representation for 3D Action Recognition Based on Tree Structure and Reference Joints (36 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
François Brémond mainly investigates Artificial intelligence, Machine learning, Pattern recognition, Convolutional neural network and RGB color model.
His Artificial intelligence study frequently draws connections between adjacent fields such as Set.
His Machine learning research integrates issues from Key, Task, Activities of daily living and Action.
François Brémond has included themes like Optical flow and Action recognition in his Pattern recognition study.
His RGB color model research incorporates themes from Orientation, Representation, Skeleton and Frame.
His Feature extraction study integrates concerns from other disciplines, such as Histogram and Local binary patterns.
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