What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Computer vision, Facial expression and Facial recognition system.
Ioannis Patras connects Artificial intelligence with Invariant in his study.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Algorithm, Optimization problem, Real image and Probabilistic logic.
His Face, Pose and Contextual image classification study in the realm of Computer vision connects with subjects such as Voting.
In his work, Affective computing, Emotion classification, Arousal and Valence is strongly intertwined with Visualization, which is a subfield of Contextual image classification.
His Facial expression research integrates issues from Speech recognition, Face hallucination, Face detection and Landmark point.
His most cited work include:
- DEAP: A Database for Emotion Analysis ;Using Physiological Signals (1495 citations)
- Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences (473 citations)
- Spatiotemporal salient points for visual recognition of human actions (216 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Machine learning are his primary areas of study.
His study in Artificial intelligence concentrates on Facial recognition system, Discriminative model, Support vector machine, Pose and Face.
Ioannis Patras works mostly in the field of Facial recognition system, limiting it down to topics relating to Facial expression and, in certain cases, Facial muscles, Gesture and Speech recognition, as a part of the same area of interest.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Contextual image classification, Pixel, Probabilistic logic and Regression.
His study looks at the relationship between Computer vision and topics such as Salient, which overlap with Real image.
His research in Feature extraction intersects with topics in Object detection, Codebook and Feature.
He most often published in these fields:
- Artificial intelligence (74.51%)
- Pattern recognition (43.14%)
- Computer vision (30.88%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (74.51%)
- Convolutional neural network (8.82%)
- State (4.90%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Convolutional neural network, State, Machine learning and Automatic summarization.
Ioannis Patras conducted interdisciplinary study in his works that combined Artificial intelligence and Group.
His Convolutional neural network research is classified as research in Pattern recognition.
His work in Pattern recognition is not limited to one particular discipline; it also encompasses Face detection.
His study in State is interdisciplinary in nature, drawing from both Speech recognition, Word, Relation and Deep neural networks.
His Machine learning research is multidisciplinary, incorporating elements of Contextual image classification, User generated video and Multimedia forensics.
Between 2018 and 2021, his most popular works were:
- Implicit and Explicit Concept Relations in Deep Neural Networks for Multi-Label Video/Image Annotation (19 citations)
- TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition. (16 citations)
- FIVR: Fine-Grained Incident Video Retrieval (13 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
His primary scientific interests are in Artificial intelligence, Machine learning, Convolutional neural network, State and Annotation.
In his works, he undertakes multidisciplinary study on Artificial intelligence and Task analysis.
His study on Convolutional neural network is covered under Pattern recognition.
Ioannis Patras has included themes like Visualization, Face detection, Kernel and Regression in his Pattern recognition study.
His studies in State integrate themes in fields like Measure, Speech recognition, Word and Relation.
His Annotation research is multidisciplinary, relying on both Artificial neural network, Semantics and Image.
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