P. L. Joseph Raj, K. Kalimuthu^*, Sabitha Gauni, C. T. Manimegalai

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1187-1196, 2022, DOI:10.32604/iasc.2022.026052 - 03 May 2022

Abstract Speckle Reduction Anisotropic Diffusion filter which is used to despeckle ultrasound images, perform well at homogeneous region than in heterogeneous region resulting in loss of information available at the edges. Extended SRAD filter does the same, preserving better the edges in addition, compared to the existing SRAD filter. The proposed Extended SRAD filter includes the intensity of four more neighboring pixels in addition with other four that is meant for SRAD filter operation. So, a total of eight pixels are involved in determining the intensity of a single pixel. This improves despeckling performance by maintaining More >

Songbin Li^1,*, Peng Liu¹, Qiandong Yan¹, Ruiling Qian²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4999-5013, 2022, DOI:10.32604/cmc.2022.026498 - 21 April 2022

Abstract Recent convolutional neural networks (CNNs) based deep learning has significantly promoted fire detection. Existing fire detection methods can efficiently recognize and locate the fire. However, the accurate flame boundary and shape information is hard to obtain by them, which makes it difficult to conduct automated fire region analysis, prediction, and early warning. To this end, we propose a fire semantic segmentation method based on Global Position Guidance (GPG) and Multi-path explicit Edge information Interaction (MEI). Specifically, to solve the problem of local segmentation errors in low-level feature space, a top-down global position guidance module is More >

Maqsood Ahmad^1,2, Noorhaniza Wahid¹, Rahayu A Hamid¹, Saima Sadiq², Arif Mehmood³, Gyu Sang Choi^4,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5041-5058, 2022, DOI:10.32604/cmc.2022.026077 - 21 April 2022

Abstract Mental health signifies the emotional, social, and psychological well-being of a person. It also affects the way of thinking, feeling, and situation handling of a person. Stable mental health helps in working with full potential in all stages of life from childhood to adulthood therefore it is of significant importance to find out the onset of the mental disease in order to maintain balance in life. Mental health problems are rising globally and constituting a burden on healthcare systems. Early diagnosis can help the professionals in the treatment that may lead to complications if they… More >

Noureen Fatima¹, Rashid Jahangir², Ghulam Mujtaba¹, Adnan Akhunzada^3,*, Zahid Hussain Shaikh⁴, Faiza Qureshi¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4357-4374, 2022, DOI:10.32604/cmc.2022.023830 - 21 April 2022

Abstract The Coronavirus Disease 2019 (COVID-19) pandemic poses the worldwide challenges surpassing the boundaries of country, religion, race, and economy. The current benchmark method for the detection of COVID-19 is the reverse transcription polymerase chain reaction (RT-PCR) testing. Nevertheless, this testing method is accurate enough for the diagnosis of COVID-19. However, it is time-consuming, expensive, expert-dependent, and violates social distancing. In this paper, this research proposed an effective multi-modality-based and feature fusion-based (MMFF) COVID-19 detection technique through deep neural networks. In multi-modality, we have utilized the cough samples, breathe samples and sound samples of healthy as… More >

Hui Yu, Jinguang Wang^*

Journal of New Media, Vol.4, No.1, pp. 13-26, 2022, DOI:10.32604/jnm.2022.027312 - 21 April 2022

Abstract With the speedy development of communication Internet and the widespread use of social multimedia, so many creators have published posts on social multimedia platforms that fake news detection has already been a challenging task. Although some works use deep learning methods to capture visual and textual information of posts, most existing methods cannot explicitly model the binary relations among image regions or text tokens to mine the global relation information in a modality deeply such as image or text. Moreover, they cannot fully exploit the supplementary cross-modal information, including image and text relations, to supplement… More >

Weiwei Cai^1,2, Yaping Song¹, Huan Duan¹, Zhenwei Xia¹, Zhanguo Wei^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1539-1555, 2022, DOI:10.32604/cmes.2022.019785 - 19 April 2022

Abstract In the smart logistics industry, unmanned forklifts that intelligently identify logistics pallets can improve work efficiency in warehousing and transportation and are better than traditional manual forklifts driven by humans. Therefore, they play a critical role in smart warehousing, and semantics segmentation is an effective method to realize the intelligent identification of logistics pallets. However, most current recognition algorithms are ineffective due to the diverse types of pallets, their complex shapes, frequent blockades in production environments, and changing lighting conditions. This paper proposes a novel multi-feature fusion-guided multiscale bidirectional attention (MFMBA) neural network for logistics… More >

M. L. Ramamoorthy¹, S. Selvaperumal^2,*, G. Prabhakar³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 485-497, 2022, DOI:10.32604/iasc.2022.025824 - 15 April 2022

Abstract The scope of this research is to design and fuse the sensors used in the self-balancing vehicle through Adaptive Neuro-Fuzzy Inference systems (ANFIS) algorithm to optimize the output. The self-balancing vehicle is a wheeled inverted pendulum, which is extremely complex, nonlinear and unstable. Homogeneous and Heterogeneous sensors are involved in this sensor fusion research to identify the best feasible value among them. The data fusion algorithm present inside the controller of the self-balancing vehicle makes the inputs of the homogeneous sensors and heterogeneous sensors separately for ameliorate surrounding perception. Simulation is performed by modeling the… More >

Jianlu Cheng¹, Kaiyong Hu^1,*, Jiang Shen¹, Lu Jia^1,2, Rui Niu¹, Zhaoxian Yang³

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.4, pp. 1049-1066, 2022, DOI:10.32604/fdmp.2022.019007 - 06 April 2022

Abstract The use of ammonia in large-scale refrigeration systems (such as those used for a stadium) requires adequate ammonia leakage prevention mechanisms are put in place. In the present study, numerical simulations have been conducted to study the dispersion law in the ammonia machinery room of the refrigeration system for the 2022 Beijing Winter Olympics. The wind speed, and release location have been varied to investigate their effects on the dispersion profile. Different positions of the leakage points in the ammonia storage tank have been found to lead to different areas affected accordingly. In general, the More >

Xiaosha Qi¹, Genlin Ji^2,*, Jie Zhang², Bo Sheng³

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1861-1875, 2022, DOI:10.32604/iasc.2022.027182 - 24 March 2022

Abstract Video anomaly detection is essential to distinguish abnormal events in large volumes of surveillance video and can benefit many fields such as traffic management, public security and failure detection. However, traditional video anomaly detection methods are unable to accurately detect and locate abnormal events in real scenarios, while existing deep learning methods are likely to omit important information when extracting features. In order to avoid omitting important features and improve the accuracy of abnormal event detection and localization, this paper proposes a novel method called Multi Chunk Learning based Skip Connected Convolutional Auto Encoder (MCSCAE).… More >

Ye Yang¹, Dongjie Zhu^2,*, Xiaofang Li³, Haiwen Du⁴, Yundong Sun⁴, Zhixin Huo², Mingrui Wu², Ning Cao¹, Russell Higgs⁵

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1379-1391, 2022, DOI:10.32604/iasc.2022.025181 - 24 March 2022

Abstract In recent years, graph representation learning has played a huge role in the fields and research of node clustering, node classification, link prediction, etc., among which many excellent models and methods have emerged. These methods can achieve better results for model training and verification of data in a single space domain. However, in real scenarios, the solution of cross-domain problems of multiple information networks is very practical and important, and the existing methods cannot be applied to cross-domain scenarios, so we research on cross-domain representation is based on multi-network space integration. This paper conducts representation More >