What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of study are Artificial intelligence, Computer vision, Digital watermarking, Image processing and Watermark. Feature extraction, Robustness, Computer graphics, Facial expression and Transform coding are the subjects of his Artificial intelligence studies. His research in Computer vision tackles topics such as Signal processing which are related to areas like Direction vector.
The concepts of his Digital watermarking study are interwoven with issues in Vector graphics, Theoretical computer science, Data mining and Authentication. His research in Watermark intersects with topics in Markov chain and Information protection policy. His Digital image study incorporates themes from Embedding and Real image.
His most cited work include:
- Robust audio watermarking in the time domain (466 citations)
- Robust image watermarking in the spatial domain (459 citations)
- Video shot detection and condensed representation. a review (239 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, Pattern recognition, Digital watermarking and Facial recognition system. His is doing research in Feature extraction, Video tracking, Cluster analysis, Stereoscopy and Support vector machine, both of which are found in Artificial intelligence. His research in Image processing, Face, Tracking, Histogram and Image are components of Computer vision.
His Pattern recognition research includes themes of Contextual image classification and Matrix decomposition. His Digital watermarking research includes elements of Watermark, Chaotic, Theoretical computer science and Robustness. His biological study spans a wide range of topics, including Detection theory and Audio signal.
He most often published in these fields:
- Artificial intelligence (76.89%)
- Computer vision (57.55%)
- Pattern recognition (33.02%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (76.89%)
- Computer vision (57.55%)
- Pattern recognition (33.02%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Computer vision, Pattern recognition, Drone and Cinematography. His study in Stereoscopy, Shot, Automatic summarization, Visualization and Support vector machine is carried out as part of his studies in Artificial intelligence. His specific area of interest is Computer vision, where Nikos Nikolaidis studies Video tracking.
His Video tracking study integrates concerns from other disciplines, such as Eye tracking and BitTorrent tracker. His study in Pattern recognition is interdisciplinary in nature, drawing from both Computational complexity theory, Facial recognition system and Image. His Image study combines topics in areas such as Similarity and Detector.
Between 2015 and 2021, his most popular works were:
- High-Level Multiple-UAV Cinematography Tools for Covering Outdoor Events (29 citations)
- Challenges in Autonomous UAV Cinematography: An Overview (22 citations)
- 2D visual tracking for sports UAV cinematography applications (12 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Nikos Nikolaidis mainly investigates Artificial intelligence, Cinematography, Computer vision, Drone and Visualization. His study brings together the fields of Pattern recognition and Artificial intelligence. His work carried out in the field of Pattern recognition brings together such families of science as Facial recognition system and Manifold.
Nikos Nikolaidis combines subjects such as Field and Shot with his study of Cinematography. His work in the fields of Computer vision, such as Stereoscopy, Video tracking and Tracking, overlaps with other areas such as Focal length. His Cluster analysis research includes elements of Speech recognition, Segmentation, Speaker diarisation and Feature.
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