Mohammed Ghanbari mainly investigates Artificial intelligence, Computer vision, Video quality, Data compression and Algorithm. His research in Artificial intelligence tackles topics such as Coding which are related to areas like Multimedia and Set partitioning in hierarchical trees. His study in Computer vision is interdisciplinary in nature, drawing from both Decimation and Signal.
His Video quality research incorporates elements of Image quality, Frame rate, Computer network and Packet switching. His Data compression research includes themes of Transform coding, Real-time computing, Reduction and Transcoding. In his research on the topic of Algorithm, Codec, Frequency domain, Variable-length code and Theoretical computer science is strongly related with Discrete cosine transform.
Mohammed Ghanbari focuses on Computer network, Artificial intelligence, Real-time computing, Computer vision and Video quality. Mohammed Ghanbari interconnects Wireless and The Internet in the investigation of issues within Computer network. His Artificial intelligence study often links to related topics such as Pattern recognition.
His research integrates issues of Codec, Communication channel, Asynchronous Transfer Mode, WiMAX and Scalable Video Coding in his study of Real-time computing. His Codec study integrates concerns from other disciplines, such as Algorithm and Coding. His Video quality research is multidisciplinary, incorporating perspectives in Bluetooth, Decoding methods, Broadband networks and Network congestion.
The scientist’s investigation covers issues in Computer network, Real-time computing, Network packet, Video quality and Codec. His studies in Computer network integrate themes in fields like Wireless network, Wireless broadband and WiMAX. His Real-time computing research focuses on Scalable Video Coding and how it relates to Multiview Video Coding, Video tracking and Uncompressed video.
His Network packet study incorporates themes from Quality of service, Flexible Macroblock Ordering, Wireless WAN and Propagation of uncertainty. His Video quality research incorporates themes from Wireless, Forward error correction, Access network and Broadband networks. His study in Codec is interdisciplinary in nature, drawing from both Image quality, Discrete cosine transform, Data compression, Computer vision and Coding.
Mohammed Ghanbari mostly deals with Video quality, Computer network, Codec, Real-time computing and Network packet. His Video quality study combines topics from a wide range of disciplines, such as Incentive, Multiple encryption and Artificial intelligence. Mohammed Ghanbari specializes in Artificial intelligence, namely Pixel.
His Codec research incorporates elements of Image quality, Discrete cosine transform, Computer vision, Algorithm and Coding. His Pattern recognition research extends to Computer vision, which is thematically connected. The study incorporates disciplines such as Scalable Video Coding and Decoding methods in addition to Real-time computing.
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Scope of validity of PSNR in image/video quality assessment
Q. Huynh-Thu;M. Ghanbari.
Electronics Letters (2008)
The cross-search algorithm for motion estimation (image coding)
IEEE Transactions on Communications (1990)
Standard Codecs: Image Compression to Advanced Video Coding
Two-layer coding of video signals for VBR networks
IEEE Journal on Selected Areas in Communications (1989)
Heterogeneous video transcoding to lower spatio-temporal resolutions and different encoding formats
T. Shanableh;M. Ghanbari.
IEEE Transactions on Multimedia (2000)
A frequency-domain video transcoder for dynamic bit-rate reduction of MPEG-2 bit streams
P.A.A. Assuncao;M. Ghanbari.
IEEE Transactions on Circuits and Systems for Video Technology (1998)
Video Coding: An Introduction to Standard Codecs
Cell-loss concealment in ATM video codecs
M. Ghanbari;V. Seferidis.
IEEE Transactions on Circuits and Systems for Video Technology (1993)
Interval Type-2 Fuzzy Logic Congestion Control for Video Streaming Across IP Networks
E.A. Jammeh;M. Fleury;C. Wagner;H. Hagras.
IEEE Transactions on Fuzzy Systems (2009)
The accuracy of PSNR in predicting video quality for different video scenes and frame rates
Quan Huynh-Thu;Mohammed Ghanbari.
Telecommunication Systems (2012)
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