2008 - IEEE Fellow For contributions to image and multimedia signal processing
The Canadian Academy of Engineering
His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Computer network. His study in Image processing, Image retrieval, Artificial neural network, Evolutionary computation and Image restoration is carried out as part of his studies in Artificial intelligence. His Pattern recognition study frequently links to other fields, such as Facial expression.
His study in the field of Biometrics, Median filter and Segmentation is also linked to topics like Boundary. His Feature extraction research is multidisciplinary, incorporating perspectives in Speech recognition, Facial recognition system, Wavelet transform, Discriminative model and Feature selection. The Resource allocation, Cache and Dynamic network analysis research Ling Guan does as part of his general Computer network study is frequently linked to other disciplines of science, such as Popularity, therefore creating a link between diverse domains of science.
Ling Guan mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Artificial neural network. Ling Guan regularly links together related areas like Machine learning in his Artificial intelligence studies. His biological study spans a wide range of topics, including Facial recognition system, Image and Feature.
Computer vision is closely attributed to Adaptive filter in his work. Ling Guan interconnects Contextual image classification, Speech recognition, Wavelet transform and Pattern recognition in the investigation of issues within Feature extraction. His work on Information retrieval expands to the thematically related Image retrieval.
Ling Guan focuses on Artificial intelligence, Pattern recognition, Discriminative model, Feature extraction and Canonical correlation. His Artificial intelligence research incorporates themes from Machine learning and Computer vision. His work deals with themes such as Image and Representation, which intersect with Pattern recognition.
The concepts of his Discriminative model study are interwoven with issues in Quadtree, Speech recognition, Coding and Cognitive neuroscience of visual object recognition. His study in the field of Handwriting recognition also crosses realms of Set. His Canonical correlation research incorporates elements of Information fusion, Facial recognition system, Face and Data set.
Ling Guan mostly deals with Artificial intelligence, Pattern recognition, Discriminative model, Canonical correlation and Feature extraction. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Graph and Computer vision. His work on Cave automatic virtual environment as part of general Computer vision research is frequently linked to Action recognition and Cave, bridging the gap between disciplines.
His work on Neural coding as part of general Pattern recognition study is frequently linked to Locality, therefore connecting diverse disciplines of science. His study explores the link between Discriminative model and topics such as Speech recognition that cross with problems in Multiview learning and Information fusion. His work investigates the relationship between Feature extraction and topics such as Representation that intersect with problems in Motion, Feature, Sample and Depth map.
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Optimal Scheduling for Charging and Discharging of Electric Vehicles
Yifeng He;B. Venkatesh;Ling Guan.
IEEE Transactions on Smart Grid (2012)
A CAD system for the automatic detection of clustered microcalcifications in digitized mammogram films
Songyang Yu;Ling Guan.
IEEE Transactions on Medical Imaging (2000)
Recognizing Human Emotional State From Audiovisual Signals
Yongjin Wang;Ling Guan.
IEEE Transactions on Multimedia (2008)
Appliance Scheduling Optimization in Smart Home Networks
F. A. Qayyum;M. Naeem;A. S. Khwaja;A. Anpalagan.
IEEE Access (2015)
Kernel Cross-Modal Factor Analysis for Information Fusion With Application to Bimodal Emotion Recognition
Yongjin Wang;Ling Guan;A. N. Venetsanopoulos.
IEEE Transactions on Multimedia (2012)
Image retrieval based on energy histograms of the low frequency DCT coefficients
J.A. Lay;Ling Guan.
international conference on acoustics speech and signal processing (1999)
Optimal resource allocation for multimedia cloud based on queuing model
Xiaoming Nan;Yifeng He;Ling Guan.
multimedia signal processing (2011)
An interactive approach for CBIR using a network of radial basis functions
P. Muneesawang;Ling Guan.
IEEE Transactions on Multimedia (2004)
A neural network approach for human emotion recognition in speech
M.W. Bhatti;Yongjin Wang;Ling Guan.
international symposium on circuits and systems (2004)
Quantifying and recognizing human movement patterns from monocular video Images-part I: a new framework for modeling human motion
R.D. Green;Ling Guan.
IEEE Transactions on Circuits and Systems for Video Technology (2004)
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