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4. A Quantitative Measurement Method for Nuclear-Pleomorphism Scoring in Breast Cancer.

Author

Teoh, Chai Ling, Tan, Xiao Jian, Ab Rahman, Khairul Shakir, Bakrin, Ikmal Hisyam, Goh, Kam Meng, Siet, Joseph Jiun Wen, and Wan Muhamad, Wan Zuki Azman

Subjects
BREAST cancer, QUANTITATIVE research, HISTOPATHOLOGY, EQUATIONS, MOTIVATION (Psychology)
Abstract

Background/Objectives: Nuclear pleomorphism, a crucial determinant of breast cancer grading under the Nottingham Histopathology Grading (NHG) system, remains inadequately quantified in the existing literature. Motivated by this gap, our study seeks to investigate and establish correlations among morphological features across various scores of nuclear pleomorphism, as per the NHG system. We aim to quantify nuclear pleomorphism across these scores and validate our proposed measurement method against ground-truth data. Methods: Initially, we deconstruct the descriptions of nuclear pleomorphism into three core elements: size, shape, and appearance. These elements are subsequently mathematically modeled into equations, termed E S i z e , E S h a p e , and E A p p e a r a n c e . These equations are then integrated into a unified model termed Harmonic Mean (HM). The HM equation yields a value approaching 1 for nuclei demonstrating characteristics of score-3 nuclear pleomorphism and near 0 for those exhibiting features of score-1 nuclear pleomorphism. Results: The proposed HM model demonstrates promising performance metrics, including Accuracy, Recall, Specificity, Precision, and F1-score, with values of 0.97, 0.96, 0.97, 0.94, and 0.95, respectively. Conclusions: In summary, this study proposes the HM equation as a novel feature for the precise quantification of nuclear pleomorphism in breast cancer. [ABSTRACT FROM AUTHOR]

Published
2024
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5. Wiper Arm Recognition Using YOLOv4

Author

Ling, Hua Jian, Goh, Kam Meng, Lai, Weng Kin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Mantoro, Teddy, editor, Lee, Minho, editor, Ayu, Media Anugerah, editor, Wong, Kok Wai, editor, and Hidayanto, Achmad Nizar, editor

Published
2021
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11. Feature Extraction for the Identification of Two-Class Mechanical Stability Test of Natural Rubber Latex

Author

Lai, Weng Kin, Chan, Kee Sum, Chan, Chee Seng, Goh, Kam Meng, Wong, Jee Keen Raymond, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Liu, Derong, editor, Xie, Shengli, editor, Li, Yuanqing, editor, Zhao, Dongbin, editor, and El-Alfy, El-Sayed M., editor

Published
2017
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20. Convolutional Neural Network based Rotten Fruit Detection using ResNet50

Author

Lim L. Tze, Chai C. Foong, and Goh Kam Meng

Subjects
Food industry, business.industry, Computer science, Deep learning, Feature extraction, food and beverages, Artificial intelligence, Healthy diet, business, Machine learning, computer.software_genre, computer, Convolutional neural network
Abstract

Food contains essential nutrients for human beings to grow and develop. Out of so many type of food, vegetables and fruits are important for humans’ daily healthy diet as they provide all the nutrients that helps human to prevent diseases. However, fruit will get rotten easily if not store properly due to the spread of bacteria. Therefore, it is important for food industry to perform inspection on fruits before selling to the consumers. The problem encountered in the human inspection is lower in consistency and accuracy as the manual inspection by humans’ eye will consume time and energy. To solve this problem, the proposed method is to apply the deep learning technique which is Convolutional Neural Networks (CNNs) for feature extraction and classification of rotten fruits. The types of fruits that will be detected and classified in this paper are banana, apple and orange. The validation accuracy obtained in this paper is 98.89%. The total duration of training stage is 212.13 minutes. Hence, the required time to classify single fruit image is approximately 0.2 second.

Published
2021

23. HEVC 2D-DCT architectures comparison for FPGA and ASIC implementations

Author

Ainy Haziyah Awab, Goh Kam Meng, Izam Kamisian, Mohd Shahrizal Rusli, Ab Al-Hadi Ab Rahman, and Usman Ullah Sheikh

Subjects
HEVC, Computer science, ASIC, DCT, 020206 networking & telecommunications, 02 engineering and technology, Energy consumption, low energy, Application-specific integrated circuit, Computer architecture, 0202 electrical engineering, electronic engineering, information engineering, Discrete cosine transform, Verilog, 020201 artificial intelligence & image processing, Electrical and Electronic Engineering, Routing (electronic design automation), Hardware_ARITHMETICANDLOGICSTRUCTURES, Field-programmable gate array, Implementation, computer, Hardware_REGISTER-TRANSFER-LEVELIMPLEMENTATION, Energy (signal processing), FPGA, computer.programming_language
Abstract

This paper compares ASIC and FPGA implementations of two commonly used architectures for 2-dimensional discrete cosine transform (DCT), the parallel and folded architectures. The DCT has been designed for sizes 4x4, 8x8, and 16x16, and implemented on Silterra 180nm ASIC and Xilinx Kintex Ultrascale FPGA. The objective is to determine suitable low energy architectures to be used as their characteristics greatly differ in terms of cells usage, placement and routing methods on these platforms. The parallel and folded DCT architectures for all three sizes have been designed using Verilog HDL, including the basic serializer-deserializer input and output. Results show that for large size transform of 16x16, ASIC parallel architecture results in roughly 30% less energy compared to folded architecture. As for FPGAs, folded architecture results in roughly 34% less energy compared to parallel architecture. In terms of overall energy consumption between 180nm ASIC and Xilinx Ultrascale, ASIC implementation results in about 58% less energy compared to the FPGA.

Published
2019

25. Size Characterisation of Edible Bird Nest Impurities: A Preliminary Study

Author

Goh Kam Meng, Daniel Koe, Lai Weng Kin, Ting Por Han, and Wong Jee Keen Raymond

Subjects
Nest, Computer science, 010401 analytical chemistry, 0202 electrical engineering, electronic engineering, information engineering, General Earth and Planetary Sciences, 020201 artificial intelligence & image processing, 02 engineering and technology, Agricultural engineering, Bird nest, 01 natural sciences, 0104 chemical sciences, General Environmental Science
Abstract

Edible bird nest (EBN) production is a major industry in South East Asia, motivated by the perception that consumption of this delicacy can help improve the human immune system while slowing down the aging process. However, processing the raw EBN requires a tremendous amount of human effort, making it a very labour-intensive process. The most critical part of this process is the cleaning of the EBN and this is also the most labour intensive and time consuming. Impurities in each sample have to be painstakingly identified and then removed from the rest of the nest. This paper proposed a method to detect the impurities in edible bird nest using K-Means segmentation to help improve the effectiveness of the conventional cleaning process by accurately identifying the impurities of various shapes and sizes. The accuracy of the proposed method has been compared with Fuzzy C-Means.

Published
2017

26. Feature Pruning for Partial Discharge Classification using IndFeat and ReliefF Algorithm

Author

Ab Halim Abu Bakar, Goh Kam Meng, Hazlee Azil Illias, Lai Weng Kin, Lau Theng Sing, and Wong Jee Keen Raymond

Subjects
010302 applied physics, Materials science, Artificial neural network, Dimensionality reduction, Feature extraction, Bandwidth (signal processing), 02 engineering and technology, 01 natural sciences, Support vector machine, 0103 physical sciences, Partial discharge, Principal component analysis, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Algorithm, Classifier (UML)
Abstract

In this work, feature pruning was implemented to a Partial Discharge (PD) classification system to reduce the size of input data. Reducing the input data feature size will ease the computational burden and reduce the data bandwidth required, which is important for real-time fault classification application. Different insulation defects will produce different PD patterns; hence PD pattern recognition is of interest to researchers worldwide because it enables the precognition of any incipient faults. PD data used in this work were obtained from 5 cross-linked polyethylene (XLPE) cables with artificial cable joint defects. Statistical features were calculated from the measured phased-resolved PD (PRPD) data. Two feature pruning algorithms, Independent Significant Feature Test (IndFeat) and ReliefF were used to decrease the dimension of input data for the classifier training process. Support Vector Machine (SVM) and Artificial Neural Network (ANN) were used as the classifier. Results show that when using the pruned data compared to unpruned data, the PD classifier was able to achieve similar performance even in the presence of noise contamination. The feature pruning algorithms also performed better compared to dimensionality reduction method such as principal component analysis (PCA).

Published
2018

30. Hardware design of a scalable and fast 2-D hadamard transform for HEVC video encoder

Author

Ab Al-Hadi Ab Rahman, Goh Kam Meng, Heh Whit Ney, Ainy Haziyah Awab, Usman Ullah Sheikh, and Mohd Shahrizal Rusli

Subjects
Hardware architecture, Loop unrolling, Control and Optimization, Computer Networks and Communications, Computer science, business.industry, Rate–distortion optimization, Hardware and Architecture, Hadamard transform, Signal Processing, Hardware acceleration, Electrical and Electronic Engineering, Field-programmable gate array, business, Encoder, Computer hardware, Information Systems, Block (data storage)
Abstract

This paper presents the hardware design of a 2-dimensional Hadamard transform used the in the rate distortion optimization module in state-of-the-art HEVC video encoder. The transform is mainly used to quickly determine optimum block size for encoding part of a video frame. The proposed design is both scalable and fast by 1) implementing a unified architecture for sizes 4x4 to 32x32, and 2) pipelining and feed through control that allows high performance for all block sizes. The design starts with high-level algorithmic loop unrolling optimization to determine suitable level of parallelism. Based on this, a suitable hardware architecture is devised using transpose memory buffer as pipeline memory for maximum performance. The design is synthesized and implemented on Xilinx Kintex Ultrascale FPGA. Results indicate variable performance obtained for different block sizes and higher operating frequency compared to a similar work in literature. The proposed design can be used as a hardware accelerator to speed up the rate distortion optimization operation in HEVC video encoders.

Published
2019

35. HEVC 2D-DCT architectures comparison for FPGA and ASIC implementations.

Author

Awab, Ainy Haziyah, Rahman, Ab Al-Hadi Ab, Rusli, Mohd Shahrizal, Sheikh, Usman Ullah, Kamisian, Izam, and Goh Kam Meng

Subjects
DISCRETE cosine transforms, FIELD programmable gate arrays, PARALLEL processing, ARCHITECTURE, ENERGY consumption
Abstract

This paper compares ASIC and FPGA implementations of two commonly used architectures for 2-dimensional discrete cosine transform (DCT), the parallel and folded architectures. The DCT has been designed for sizes 4x4, 8x8, and 16x16, and implemented on Silterra 180nm ASIC and Xilinx Kintex Ultrascale FPGA. The objective is to determine suitable low energy architectures to be used as their characteristics greatly differ in terms of cells usage, placement and routing methods on these platforms. The parallel and folded DCT architectures for all three sizes have been designed using Verilog HDL, including the basic serializer-deserializer input and output. Results show that for large size transform of 16x16, ASIC parallel architecture results in roughly 30% less energy compared to folded architecture. As for FPGAs, folded architecture results in roughly 34% less energy compared to parallel architecture. In terms of overall energy consumption between 180nm ASIC and Xilinx Ultrascale, ASIC implementation results in about 58% less energy compared to the FPGA. [ABSTRACT FROM AUTHOR]

Published
2019
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39. A Brief Simulation Method for Coded Structured Light Based 3D Reconstruction

Author

Wang, Nianfeng, Xie, Weiyong, Zhong, Kaifan, Zhang, Xianmin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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40. An Automated View Planning Method of Robot 3D Measurement

Author

Yang, Yilin, Zhang, Lin, Wu, Zeping, Zhang, Xu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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41. A Method for Welding Track Correction Based on Emulational Laser and Trajectory

Author

Wang, Nianfeng, Yang, Jialin, Zhong, Kaifan, Zhang, Xianmin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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42. A Novel Edge Detection and Localization Method of Depalletizing Robot

Author

Liu, Weihong, Gao, Yang, Wang, Yong, Liu, Zhe, Chen, Diansheng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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43. A Self-correction Based Algorithm for Single-Shot Camera Calibration

Author

Yu, Shuangfei, Hong, Jie, Zhang, Tao, Yang, Zhi, Guan, Yisheng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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44. Control of a Series Elastic Actuator Based on Sigmoid-Proportional-Retarded (SPR) with Online Gravity Compensation

Author

Jiang, Feng, Zhang, Jiexin, Zhang, Bo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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45. Human Gait Analysis Method Based on Kinect Sensor

Author

Wang, Nianfeng, Lin, Guifeng, Zhang, Xianmin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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46. Research on Point Cloud Processing Algorithm Applied to Robot Safety Detection

Author

Wang, Nianfeng, Lin, Jingxin, Zhong, Kaifan, Zhang, Xianmin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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47. A Flexible Mechanical Arm Based on Miura-Ori

Author

Zhang, Xiu, Yu, Meng, Yang, Weimin, Yu, Yuan, Ding, Yumei, Jiao, Zhiwei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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48. Multi-scale Crack Detection Based on Keypoint Detection and Minimal Path Technique

Author

Wang, Nianfeng, Zhu, Hao, Zhang, Xianmin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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49. 6D Pose Estimation for Texture-Less Industrial Parts in the Crowd

Author

Zhou, Dexin, Chai, Ziqi, Liu, Chao, Li, Peng, Xiong, Zhenhua, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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50. The Point Position and Normal Detection System and Its Application

Author

Yun, Jin, Chen, Li, Xu, Zhang, Dawei, Tu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chan, Chee Seng, editor, Liu, Hong, editor, Zhu, Xiangyang, editor, Lim, Chern Hong, editor, Liu, Xinjun, editor, Liu, Lianqing, editor, and Goh, Kam Meng, editor

Published
2020
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