Jung H. Kim

TitleProfessor

DepartmentElectrical and Computer Engineering

Phone336-285-3713

Fax336-334-7716

Emailkim@ncat.edu

OfficeMcNair Hall
Room: 535

1601 East Market Street
Greensboro, NC 27411

Jung H. Kim

Education

Ph D: Electrical and Computer Engineering, North Carolina State University, 1985

MS: Electrical and Computer Engineering, North Carolina State University, 1982

BS: Electronics, Yonsei University, Korea, 1974


Research Interests

Dr. Kim has many experience in the areas of computer vision, digital signal and image processing algorithms and advanced techniques for the robust recognition of partially occluded objects in a multi-context scene by using Neural Networks and Pattern Recognition. Current research of his interest includes object and pattern recognition, signal and image processing, video transmission, genomic data analysis and wireless sensor networks.


Recent Publications

Ismail, H  Jones, Adri-Anne  Kim, Jung  Newman, Robert  Kc, Dukka  (2016).  RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest..  (2016,  pp. 3281590).  BioMed research international.

Bhatti, Ali  Kim, Jung  (2015).  Lossless Huffman coding for image compression and decompression based on block and code book size using K-Means algorithm in spatial and frequency domain.  (Issue 10,  vol.6,  pp. pp503-520).  International Journal of Scientific & Engineering Research.

Bhatti, Ali  Kim, Jung  (2015).  R-Peak detection in ECG signal compression for Heartbeat rate patients at 1KHz using High Order Statistic Algorithm.  (9,  2,  pp. pp2509-2515).  Journal of Multidisciplinary Engineering Science and Technology (JMEST).

Bhatti, Ali  Kim, Jung  (2015).  Implementation of Lossless Huffman Coding: Image compression using K-Means algorithm and comparison vs. Random numbers and Message source.  (05,  02,  pp. pp497-505).  International Research Journal of Engineering and Technology (IRJET).

Bhatti, Ali  Kim, Jung  (2015).  Implementation of Reed-Solomon (RS) and CDMA for signaling a voice through AWGN at 8 KHz sampling frequency using BPSK.  (05,  2,  pp. pp13-27).  รข€, International Journal of Advent Research in Computer and Electronics (IJARCE).