His primary scientific interests are in Artificial intelligence, Pattern recognition, Computer vision, Artificial neural network and Radar. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Data mining. His work in Pattern recognition addresses subjects such as Face detection, which are connected to disciplines such as Color model.
His work in the fields of Computer vision, such as Color histogram and Pixel, overlaps with other areas such as Spectral line. His research integrates issues of Shunting, Inhibitory postsynaptic potential, Feature extraction, Convolutional neural network and Topology in his study of Artificial neural network. The various areas that Abdesselam Bouzerdoum examines in his Radar study include Classification methods, Gait and Spectrogram.
Artificial intelligence, Computer vision, Pattern recognition, Artificial neural network and Radar are his primary areas of study. His works in Feature extraction, Image segmentation, Convolutional neural network, Deep learning and Pixel are all subjects of inquiry into Artificial intelligence. His work on Image quality, Motion detection and Image processing as part of general Computer vision study is frequently linked to Object detection, bridging the gap between disciplines.
His work deals with themes such as Contextual image classification, Face detection and Feature, which intersect with Pattern recognition. Artificial neural network is a subfield of Machine learning that Abdesselam Bouzerdoum explores. Abdesselam Bouzerdoum focuses mostly in the field of Radar, narrowing it down to matters related to Signal and, in some cases, Ground-penetrating radar.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Deep learning and Radar. All of his Artificial intelligence and Feature extraction, Artifact, Image, Regularization and Feature investigations are sub-components of the entire Artificial intelligence study. His Pattern recognition research is multidisciplinary, relying on both Frame and Vector autoregression.
His Computer vision research incorporates themes from Artificial neural network, Inference, Trajectory and Sonar. Abdesselam Bouzerdoum interconnects Classifier and Convolutional neural network in the investigation of issues within Deep learning. His study in the field of Clutter is also linked to topics like Object detection.
Abdesselam Bouzerdoum focuses on Artificial intelligence, Deep learning, Convolutional neural network, Pattern recognition and Image processing. His Artificial intelligence research includes elements of Radar, White matter and Computer vision. Many of his research projects under Radar are closely connected to Sparse matrix with Sparse matrix, tying the diverse disciplines of science together.
His Computer vision research is multidisciplinary, incorporating perspectives in Detector and Sonar. His Convolutional neural network research includes themes of Transfer of learning and Recall rate. His work on Segmentation, Image segmentation and Classifier as part of general Pattern recognition study is frequently connected to Gaussian process, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
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Skin segmentation using color pixel classification: analysis and comparison
S.L. Phung;A. Bouzerdoum;D. Chai.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2005)
A novel skin color model in YCbCr color space and its application to human face detection
Son Lam Phung;A. Bouzerdoum;D. Chai.
international conference on image processing (2002)
Neural network for quadratic optimization with bound constraints
A. Bouzerdoum;T.R. Pattison.
IEEE Transactions on Neural Networks (1993)
A Bayesian approach to skin color classification in YCbCr color space
D. Chai;A. Bouzerdoum.
ieee region 10 conference (2000)
Learning Pattern Classification Tasks with Imbalanced Data Sets
Giang Hoang Nguyen;Abdesselam Bouzerdoum;Son Lam Phung.
Shunting inhibitory cellular neural networks: derivation and stability analysis
A. Bouzerdoum;R.B. Pinter.
IEEE Transactions on Circuits and Systems I-regular Papers (1993)
A Pyramidal Neural Network For Visual Pattern Recognition
S.L. Phung;A. Bouzerdoum.
IEEE Transactions on Neural Networks (2007)
A generalized feedforward neural network architecture for classification and regression
Ganesh Arulampalam;Abdesselam Bouzerdoum.
international joint conference on neural network (2003)
A Subspace Projection Approach for Wall Clutter Mitigation in Through-the-Wall Radar Imaging
Fok Hing Chi Tivive;Abdesselam Bouzerdoum;Moeness G. Amin.
IEEE Transactions on Geoscience and Remote Sensing (2015)
An insect vision-based motion detection chip
A. Moini;A. Bouzerdoum;K. Eshraghian;A. Yakovleff.
IEEE Journal of Solid-state Circuits (1997)
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