Lili Pan¹, Jiaohua Qin^1,*, Hao Chen², Xuyu Xiang¹, Cong Li¹, Ran Chen¹

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 297-313, 2019, DOI:10.32604/cmc.2019.04097

Abstract Image retrieval for food ingredients is important work, tremendously tiring, uninteresting, and expensive. Computer vision systems have extraordinary advancements in image retrieval with CNNs skills. But it is not feasible for small-size food datasets using convolutional neural networks directly. In this study, a novel image retrieval approach is presented for small and medium-scale food datasets, which both augments images utilizing image transformation techniques to enlarge the size of datasets, and promotes the average accuracy of food recognition with state-of-the-art deep learning technologies. First, typical image transformation techniques are used to augment food images. Then transfer learning technology based on deep… More >

M. Rajalakshmi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.2, pp. 209-220, 2018, DOI:10.3970/cmes.2018.114.209

Abstract Amongst several biometric traits, Vein pattern biometric has drawn much attention among researchers and diverse users. It gains its importance due to its difficulty in reproduction and inherent security advantages. Many research papers have dealt with the topic of new generation biometric solutions such as iris and vein biometrics. However, most implementations have been based on small datasets due to the difficulties in obtaining samples. In this paper, a deeper study has been conducted on previously suggested methods based on Convolutional Neural Networks (CNN) using a larger dataset. Also, modifications are suggested for implementation using ensemble methods. Ensembles were used… More >

R. Martin¹, D. Komatitsch^1,2, S. D. Gedney³

CMES-Computer Modeling in Engineering & Sciences, Vol.37, No.3, pp. 274-304, 2008, DOI:10.3970/cmes.2008.037.274

Abstract In the context of the numerical simulation of seismic wave propagation, the perfectly matched layer (PML) absorbing boundary condition has proven to be efficient to absorb surface waves as well as body waves with non grazing incidence. But unfortunately the classical discrete PML generates spurious modes traveling and growing along the absorbing layers in the case of waves impinging the boundary at grazing incidence. This is significant in the case of thin mesh slices, or in the case of sources located close to the absorbing boundaries or receivers located at large offset. In previous work we derived an unsplit convolutional… More >

Roland Martin¹, Carlos Couder-Castaneda¹

CMES-Computer Modeling in Engineering & Sciences, Vol.63, No.1, pp. 47-78, 2010, DOI:10.3970/cmes.2010.063.047

Abstract We develop an unsplit convolutional perfectly matched layer (CPML) technique to absorb efficiently compressible viscous flows and their related supersonic or subsonic regimes at the outer boundary of a distorted computational domain. More particularly subsonic outgoing flows or subsonic wall-boundary layers close to the PML are well absorbed, which is difficult to obtain without creating numerical instabilities over long time periods. This new PML (CPML) introduces the calculation of auxiliary memory variables at each time step and allows an unsplit formulation of the PML. Damping functions involving a high shift in the frequency domain allow a much better absorption of… More >

Xianyu Wu¹, Chao Luo¹, Qian Zhang², Jiliu Zhou¹, Hao Yang^{1, 3, *}, Yulian Li¹

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 289-300, 2019, DOI:10.32604/cmc.2019.05990

Abstract Words are the most indispensable information in human life. It is very important to analyze and understand the meaning of words. Compared with the general visual elements, the text conveys rich and high-level moral information, which enables the computer to better understand the semantic content of the text. With the rapid development of computer technology, great achievements have been made in text information detection and recognition. However, when dealing with text characters in natural scene images, there are still some limitations in the detection and recognition of natural scene images. Because natural scene image has more interference and complexity than… More >

Xin Li^1,2, Yanchun Liang^1,2, Minghao Zhao^1,2, Chong Wang^1,2,3, Yu Jiang^1,2,*

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1073-1085, 2019, DOI:10.32604/cmc.2019.05929

Abstract In recent years, extreme weather events accompanying the global warming have occurred frequently, which brought significant impact on national economic and social development. The ocean is an important member of the climate system and plays an important role in the occurrence of climate anomalies. With continuous improvement of sensor technology, we use sensors to acquire the ocean data for the study on resource detection and disaster prevention, etc. However, the data acquired by the sensor is not enough to be used directly by researchers, so we use the Generative Adversarial Network (GAN) to enhance the ocean data. We use GAN… More >

Feng Xu¹, Xuefen Zhang^2,*, Zhanhong Xin¹, Alan Yang³

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 697-709, 2019, DOI:10.32604/cmc.2019.05375

Abstract Nowadays, the amount of wed data is increasing at a rapid speed, which presents a serious challenge to the web monitoring. Text sentiment analysis, an important research topic in the area of natural language processing, is a crucial task in the web monitoring area. The accuracy of traditional text sentiment analysis methods might be degraded in dealing with mass data. Deep learning is a hot research topic of the artificial intelligence in the recent years. By now, several research groups have studied the sentiment analysis of English texts using deep learning methods. In contrary, relatively few works have so far… More >

Min Long^1,2,*, Yan Zeng¹

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 493-504, 2019, DOI:10.32604/cmc.2019.04378

Abstract Aim to countermeasure the presentation attack for iris recognition system, an iris liveness detection scheme based on batch normalized convolutional neural network (BNCNN) is proposed to improve the reliability of the iris authentication system. The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris, including convolutional layer, batch-normalized (BN) layer, Relu layer, pooling layer and full connected layer. The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels, and then the iris features are extracted by BNCNN. With these features, the genuine iris and fake iris are determined by… More >

Nianbin Wang¹, Ming He^1,2, Jianguo Sun^1,*, Hongbin Wang¹, Lianke Zhou¹, Ci Chu¹, Lei Chen³

CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 169-181, 2019, DOI:10.32604/cmc.2019.03709

Abstract Underwater target recognition is a key technology for underwater acoustic countermeasure. How to classify and recognize underwater targets according to the noise information of underwater targets has been a hot topic in the field of underwater acoustic signals. In this paper, the deep learning model is applied to underwater target recognition. Improved anti-noise Power-Normalized Cepstral Coefficients (ia-PNCC) is proposed, based on PNCC applied to underwater noises. Multitaper and normalized Gammatone filter banks are applied to improve the anti-noise capacity. The method is combined with a convolutional neural network in order to recognize the underwater target. Experiment results show that the… More >

Chuanlong Li^1,2,*, Yumeng Jiang³, Marta Cheslyar¹

CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 313-324, 2018, DOI: 10.3970/cmc.2018.03950

Abstract Deep neural network has proven to be very effective in computer vision fields. Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods. Generative adversarial network (GAN) is becoming one of the highlights among these deep neural networks. GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks. One promising application of using GAN generated images would be image concealing which requires the embedded image looks… More >