Implementation of Computer-Aided Diagnosis System on Customizable DSP Core for Colorectal Endoscopic Images with CNN Features and SVM
Takumi Okamoto, Tetsushi Koide, Shigeto Yoshida, Hiroshi Mieno, Hiroshi Toishi, Takayuki Sugawara, Masayuki Tsuji, Masayuki Odagawa, N. Tamba, Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda, Shinji Tanaka · 2018
In this paper, the computer-aided diagnosis system for colorectal endoscopic images is proposed. The proposed system is consisted of Convolutional Neural Network (CNN) as the feature extraction processing and Support Vector Machine (SVM) as identification processing. The proposed system is also implemented on customizable Digital Signal Processing (DSP) core: Vision P6 DSP and is demonstrated the effectiveness of a real-time recognition system by a FPGA based prototyping system, Protium™ S1.