M. P. Haripriya^*, P. Venkadesh

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 825-836, 2022, DOI:10.32604/iasc.2022.022940 - 08 February 2022

Abstract The coming generation in mobile networks is the fifth generation (5G), which appears to be the promoter of the upcoming digital world. 5G is defined by a single piece of cellular access technology or a combination of advanced access technologies. Rather, 5G is a true network assembler that provides consistent support for a slew of novel network topologies. Prior generations provide as a suitable starting point and give support for the security architecture for 5G security. Through authentication and cryptography techniques, many works have tackled the security issues in 3G and 4G networks in an… More >

Chengfan Li^1,2, Lan Liu^3,*, Junjuan Zhao¹, Xuefeng Liu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 429-444, 2022, DOI:10.32604/cmes.2022.019202 - 24 January 2022

Abstract Target detection of small samples with a complex background is always difficult in the classification of remote sensing images. We propose a new small sample target detection method combining local features and a convolutional neural network (LF-CNN) with the aim of detecting small numbers of unevenly distributed ground object targets in remote sensing images. The k-nearest neighbor method is used to construct the local neighborhood of each point and the local neighborhoods of the features are extracted one by one from the convolution layer. All the local features are aggregated by maximum pooling to obtain global… More >

Hilly Gohain Baruah^*, Vijay Kumar Nath, Deepika Hazarika

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 137-164, 2022, DOI:10.32604/cmes.2022.018339 - 24 January 2022

Abstract With the increasing popularity of high-resolution remote sensing images, the remote sensing image retrieval (RSIR) has always been a topic of major issue. A combined, global non-subsampled shearlet transform (NSST)-domain statistical features (NSSTds) and local three dimensional local ternary pattern (3D-LTP) features, is proposed for high-resolution remote sensing images. We model the NSST image coefficients of detail subbands using 2-state laplacian mixture (LM) distribution and its three parameters are estimated using Expectation-Maximization (EM) algorithm. We also calculate the statistical parameters such as subband kurtosis and skewness from detail subbands along with mean and standard deviation… More >

Rami Sameer Ahmad Al Kloub^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5151-5165, 2022, DOI:10.32604/cmc.2022.024309 - 14 January 2022

Abstract Flood disasters can be reliably monitored using remote sensing photos with great spatiotemporal resolution. However, satellite revisit periods and extreme weather limit the use of high spatial resolution images. As a result, this research provides a method for combining Landsat and MODIS pictures to produce high spatiotemporal imagery for flood disaster monitoring. Using the spatial and temporal adaptive reflectance fusion model (STARFM), the spatial and temporal reflectance unmixing model (STRUM), and three prominent algorithms of flexible spatiotemporal data fusion (FSDAF), Landsat fusion images are created by fusing MODIS and Landsat images. Then, to extract flood… More >

Shariq Bashir^1,*, Owais Ahmed Malik², Daphne Teck Ching Lai²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6165-6181, 2022, DOI:10.32604/cmc.2022.024269 - 14 January 2022

Abstract Traditional wireless sensor networks (WSNs) are not suitable for rough terrains that are difficult or impossible to access by humans. Smart dust is a technology that works with the combination of many tiny sensors which is highly useful for obtaining remote sensing information from rough terrains. The tiny sensors are sprinkled in large numbers on rough terrains using airborne distribution through drones or aircraft without manually setting their locations. Although it is clear that a number of remote sensing applications can benefit from this technology, but the small size of smart dust fundamentally restricts the… More >

G. Chamundeeswari¹, S. Srinivasan^1,*, S. Prasanna Bharathi^1,2

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 515-534, 2022, DOI:10.32604/iasc.2022.023449 - 05 January 2022

Abstract Remote sensing (RS) is a very reliable and effective way to monitor the environment and landscape changes. In today’s world topographic maps are very important in science, research, planning and management. It is quite possible to detect the changes based on RS data which is obtained at two different times. In this paper, we propose an optimal technique that handles problems like urban green space destruction and detection of crop stress assessment. Firstly, the optimal preprocessing is performed on the given RS dataset, for image enhancement using geometric correction and image registration. Secondly, we propose… More >

K. Saranya^1,*, K. Selva Bhuvaneswari²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 399-414, 2022, DOI:10.32604/iasc.2022.023149 - 05 January 2022

Abstract This paper presents a novel fuzzy logic based Convolution Neural Network intelligent classifier for accurate image classification. The proposed approach employs a semantic class label model that classifies the input land cover images into a set of semantic categories and classes depending on the content. The intelligent feature selection algorithm selects the prominent attributes from the given data set using weighted attribute functions and uses fuzzy logic to build the rules based on the membership values. To annotate remote sensing images, the CNN method effectively creates semantics and categorises images. The decision manager then integrates More >

Wenzheng Yu¹, Jintao Cui², Yang Gao¹, Mingxuan Zhu¹, Li Shao³, Yanbo Shen^4,5,*, Xiaozhao Zhang⁶, Chen Guo⁷, Hanxiaoya Zhang⁸

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3635-3646, 2022, DOI:10.32604/cmc.2022.023195 - 07 December 2021

Abstract Land desertification is a widely concerned ecological environment problem. Studying the evolution trend of desertification types is of great significance to prevent and control land desertification. In this study, we applied the decision tree classification method, to study the land area and temporal and spatial change law of different types of desertification in the North Bank of Qinghai Lake area from 1987 to 2014, based on the current land use situation and TM remote sensing image data of Haiyan County, Qinghai Province, The results show that the area of mild desertification land and moderate desertification… More >

Muhammad Umair¹, Fiaz Majeed¹, Muhammad Shoaib², Muhammad Qaiser Saleem³, Mohmmed S. Adrees³, Abdelrahman Elsharif Karrar⁴, Shahzada Khurram⁵, Muhammad Shafiq^6,*, Jin-Ghoo Choi⁶

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1179-1194, 2022, DOI:10.32604/iasc.2022.018952 - 17 November 2021

Abstract Citations are references used by researchers to recognize the contributions of researchers in their articles. Citations can be used to discover hidden patterns in the research domain, and can also be used to perform various analyses in data mining. Citation analysis is a quantitative method to identify knowledge dissemination and influence papers in any research area. Citation analysis involves multiple techniques. One of the most commonly used techniques is Main Path Analysis (MPA). According to the specific use of MPA, it has evolved into various variants. Currently, MPA is carried out in different domains, but… More >

Shahab Ul Islam¹, Saifullah Jan², Abdul Waheed^3,4,*, Gulzar Mehmood⁵, Mahdi Zareei⁶, Faisal Alanazi⁷

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4123-4145, 2022, DOI:10.32604/cmc.2022.019226 - 27 September 2021

Abstract Spatial and temporal information on urban infrastructure is essential and requires various land-cover/land-use planning and management applications. Besides, a change in infrastructure has a direct impact on other land-cover and climatic conditions. This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature (LST) during the years 1996 and 2019. For this purpose, firstly, satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper) plus and OLI (Operational Land Imager) of 30 m resolution were taken. Secondly, for classification and image processing, remote sensing (RS) applications… More >