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, Facial recognition system, Pattern recognition and Spoofing attack.
His study in Local binary patterns, Face, Feature extraction and Face detection are all subfields of Artificial intelligence.
FERET database is closely connected to Linear discriminant analysis in his research, which is encompassed under the umbrella topic of Feature extraction.
He is interested in Three-dimensional face recognition, which is a branch of Computer vision.
His research in Pattern recognition intersects with topics in Image quality and Histogram.
His work focuses on many connections between Spoofing attack and other disciplines, such as Biometrics, that overlap with his field of interest in Robustness and Pattern recognition.
His most cited work include:
- Face Description with Local Binary Patterns: Application to Face Recognition (4503 citations)
- Face Recognition with Local Binary Patterns (1954 citations)
- Computer Vision Using Local Binary Patterns (393 citations)
What are the main themes of his work throughout his whole career to date?
Abdenour Hadid focuses on Artificial intelligence, Pattern recognition, Face, Local binary patterns and Facial recognition system.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning, Spoofing attack and Computer vision.
His Pattern recognition study incorporates themes from Histogram and Benchmark.
In his research on the topic of Face, Pooling is strongly related with Facial expression.
His Local binary patterns research includes themes of Segmentation, Face hallucination, Feature and Image texture.
His study involves Face detection and Three-dimensional face recognition, a branch of Facial recognition system.
He most often published in these fields:
- Artificial intelligence (89.60%)
- Pattern recognition (60.69%)
- Face (45.66%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (89.60%)
- Pattern recognition (60.69%)
- Face (45.66%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Pattern recognition, Face, Deep learning and Biometrics.
Artificial intelligence is closely attributed to Machine learning in his research.
His Pattern recognition research includes elements of Local binary patterns, Facial expression, Pooling and Feature.
His studies deal with areas such as Feature vector and Image texture as well as Local binary patterns.
His Facial recognition system study combines topics in areas such as Image quality and Spoofing attack.
His study in the fields of Mel-frequency cepstrum under the domain of Feature extraction overlaps with other disciplines such as Energy.
Between 2016 and 2021, his most popular works were:
- OULU-NPU: A Mobile Face Presentation Attack Database with Real-World Variations (177 citations)
- Face Antispoofing Using Speeded-Up Robust Features and Fisher Vector Encoding (122 citations)
- A competition on generalized software-based face presentation attack detection in mobile scenarios (84 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of investigation include Artificial intelligence, Pattern recognition, Spoofing attack, Biometrics and Convolutional neural network.
His biological study spans a wide range of topics, including Machine learning and Computer vision.
His Pattern recognition research incorporates themes from Variation, Local binary patterns and Deep learning.
The Local binary patterns study which covers Image texture that intersects with Computer security and Chrominance.
His study on Spoofing attack is mostly dedicated to connecting different topics, such as Facial recognition system.
His Feature vector research is multidisciplinary, incorporating perspectives in Texture and Fingerprint.
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