Yifan Yin¹, Chunliu He¹, Biao Xu², Zhiyong Li^1,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 57-57, 2019, DOI:10.32604/mcb.2019.05732

Abstract The tissue composition and morphological structure of atherosclerotic plaques determine its stability or vulnerability. Intravascular optical coherence tomography (IVOCT) has rapidly become the method of choice for assessing the pathology of the coronary arterial wall in vivo due to its superior resolution. However, in clinical practice, the analysis of plaque composition of OCT images mainly relies on the interpretation of images by well-trained experts, which is a time-consuming, labor-intensive procedure and it is also subjective. The purpose of this study is to use the Convolutional neural network (CNN) method to automatically extract the best feature… More >

Chaoyang Xia¹, Jing Peng¹, Zongqing Ma², Xiaojie Li^1,*

Journal of Information Hiding and Privacy Protection, Vol.1, No.3, pp. 109-117, 2019, DOI:10.32604/jihpp.2019.07198

Abstract Cardiomyopathy is one of the most serious public health threats. The precise structural and functional cardiac measurement is an essential step for clinical diagnosis and follow-up treatment planning. Cardiologists are often required to draw endocardial and epicardial contours of the left ventricle (LV) manually in routine clinical diagnosis or treatment planning period. This task is time-consuming and error-prone. Therefore, it is necessary to develop a fully automated end-to-end semantic segmentation method on cardiac magnetic resonance (CMR) imaging datasets. However, due to the low image quality and the deformation caused by heartbeat, there is no effective… More >

Liming Chen¹, Bosi Wang^1,*, Weijie Yu¹, Xu Fan¹

Journal of New Media, Vol.1, No.3, pp. 115-126, 2019, DOI:10.32604/jnm.2019.08581

Abstract With the development of multimedia presentation technology, image acquisition technology and the Internet industry, long-distance communication methods have changed from the previous letter, the audio to the current audio/video. And the proportion of video in work, study and entertainment keeps increasing, high-definition video is getting more and more attention. Due to the limits of the network environment and storage capacity, the original video must be encoded to be efficiently transmitted and stored. High Efficient Video Coding (HEVC) requires a large amount of time to recursively traverse all possible quantization parameter values of the coding unit More >

Hao Wu¹, Qi Liu^{2, 3, *}, Xiaodong Liu⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 575-597, 2019, DOI:10.32604/cmc.2019.03595

Abstract Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effectively achieved large-scale deep learnt neural networks showing better performance with deeper depth and wider width of networks. With the efforts in the present deep learning approaches, factors, e.g., network structures, training methods and training data sets are playing critical roles in improving the performance of networks. In this paper, deep learning models in recent years are summarized and compared with detailed More >

Lin Zhou^1,*, Kangyu Ma¹, Lijie Wang¹, Ying Chen^1,2, Yibin Tang³

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 545-557, 2019, DOI:10.32604/cmc.2019.05969

Abstract Binaural sound source localization (BSSL) in low signal-to-noise ratio (SNR) and high reverberation environment is still a challenging task. In this paper, a novel BSSL algorithm is proposed by introducing convolutional neural network (CNN). The proposed algorithm first extracts the spatial feature of each sub-band from binaural sound signal, and then combines the features of all sub-bands within one frame to assemble a two-dimensional feature matrix as a grey image. To fully exploit the advantage of the CNN in extracting high-level features from the grey image, the spatial feature matrix of each frame is used More >

Zhong Liu^1,2, Xinan Wang^1,*, Kuntao Lu¹, David Su³

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 497-509, 2019, DOI:10.32604/cmc.2019.04882

Abstract ECG signal is of great importance in the clinical diagnosis of various heart diseases. The abnormal origin or conduction of excitation is the electrophysiological mechanism leading to arrhythmia, but the type and frequency of arrhythmia is an important indicator reflecting the stability of cardiac electrical activity. In clinical practice, arrhythmic signals can be classified according to the origin of excitation, the frequency of excitation, or the transmission of excitation. Traditional heart disease diagnosis depends on doctors, and it is influenced by doctors' professional skills and the department's specialty. ECG signal has the characteristics of weak More >

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 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 >

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… 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… More >