What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His primary scientific interests are in Artificial intelligence, Pattern recognition, Feature extraction, Facial recognition system and Artificial neural network.
His biological study spans a wide range of topics, including Zernike polynomials, Speech recognition and Computer vision.
His work carried out in the field of Computer vision brings together such families of science as Weighting and Facial expression.
His work on Pattern recognition deals in particular with Feature vector, Classifier, Wavelet transform, Haar wavelet and Support vector machine.
His Facial recognition system research includes elements of Principal component analysis and Biometrics.
His Artificial neural network study incorporates themes from Contextual image classification and Fuzzy control system, Fuzzy logic.
His most cited work include:
- Handwritten Farsi (Arabic) word recognition: a holistic approach using discrete HMM (130 citations)
- An improved feature selection method based on ant colony optimization (ACO) evaluated on face recognition system (116 citations)
- Fast Circle Detection Using Gradient Pair Vectors (95 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Artificial neural network are his primary areas of study.
His Artificial intelligence study frequently links to related topics such as Speech recognition.
His studies deal with areas such as Contextual image classification, Histogram, Zernike polynomials and Face as well as Pattern recognition.
His Computer vision study frequently involves adjacent topics like Facial expression.
His Feature extraction study combines topics from a wide range of disciplines, such as Classifier, Feature and Image processing.
His Three-dimensional face recognition, Face detection and Face hallucination study in the realm of Facial recognition system interacts with subjects such as Invariant.
He most often published in these fields:
- Artificial intelligence (70.71%)
- Pattern recognition (52.27%)
- Computer vision (32.07%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (70.71%)
- Pattern recognition (52.27%)
- Computer vision (32.07%)
In recent papers he was focusing on the following fields of study:
Karim Faez mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Algorithm.
His research related to Facial recognition system, Facial expression, Support vector machine, Face and Sparse approximation might be considered part of Artificial intelligence.
Karim Faez studies Pattern recognition, focusing on Feature vector in particular.
His research investigates the connection between Computer vision and topics such as Cluster analysis that intersect with problems in Maximally stable extremal regions and Radon transform.
His Feature extraction research is multidisciplinary, incorporating perspectives in Principal component analysis, Object detection, Speech recognition and Cognitive neuroscience of visual object recognition.
His work deals with themes such as Pixel, Chaotic, Theoretical computer science and Steganography, which intersect with Algorithm.
Between 2013 and 2021, his most popular works were:
- A digital implementation of neuron-astrocyte interaction for neuromorphic applications (37 citations)
- Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks (35 citations)
- A New Lightweight Watchdog-Based Algorithm for Detecting Sybil Nodes in Mobile WSNs (34 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Karim Faez focuses on Artificial intelligence, Pattern recognition, Computer vision, Algorithm and Facial expression.
While working on this project, he studies both Artificial intelligence and Knuckle.
His research in Pattern recognition intersects with topics in Modality and Speech recognition.
His Algorithm research includes themes of Information hiding, Pixel, Chaotic and Steganography.
Karim Faez regularly links together related areas like Feature extraction in his Facial expression studies.
His work investigates the relationship between Facial recognition system and topics such as Pose that intersect with problems in 3d model and FERET.
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