Mehrdad Shoeibi¹, Mohammad Mehdi Sharifi Nevisi², Reza Salehi³, Diego Martín^3,*, Zahra Halimi⁴, Sahba Baniasadi⁵

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3469-3493, 2024, DOI:10.32604/cmc.2024.049847

Abstract Hyperspectral (HS) image classification plays a crucial role in numerous areas including remote sensing (RS), agriculture, and the monitoring of the environment. Optimal band selection in HS images is crucial for improving the efficiency and accuracy of image classification. This process involves selecting the most informative spectral bands, which leads to a reduction in data volume. Focusing on these key bands also enhances the accuracy of classification algorithms, as redundant or irrelevant bands, which can introduce noise and lower model performance, are excluded. In this paper, we propose an approach for HS image classification using… More >

Xin Yin^1,#, Shuai Wang^1,#, Chunguang Wang¹, Haichao Wang², Zheying Zong^1,3,*, Zeyu Ban¹

Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 843-858, 2024, DOI:10.32604/phyton.2024.049114

Abstract This study employed the bibliometric software CiteSpace 6.1.R6 to analyze the correlation between thermal infrared, spectral remote sensing technology, and the estimation of economic forest water stress. It aimed to review the development and current status of this field, as well as to identify future research trends. A search was conducted on the China National Knowledge Infrastructure (CNKI) database using the keyword “water stress” for relevant studies from 2003 to 2023. The visual analysis function of CNKI was used to generate the distribution of annual publication volume, and CiteSpace 6.1.R6 was utilized to create network More >

Yaming Kang^1,*, Peishun Ye¹, Yuxiu Bai¹, Shi Qiu²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2151-2168, 2024, DOI:10.32604/cmc.2024.049360

Abstract Hyperspectral imagery encompasses spectral and spatial dimensions, reflecting the material properties of objects. Its application proves crucial in search and rescue, concealed target identification, and crop growth analysis. Clustering is an important method of hyperspectral analysis. The vast data volume of hyperspectral imagery, coupled with redundant information, poses significant challenges in swiftly and accurately extracting features for subsequent analysis. The current hyperspectral feature clustering methods, which are mostly studied from space or spectrum, do not have strong interpretability, resulting in poor comprehensibility of the algorithm. So, this research introduces a feature clustering algorithm for hyperspectral… More >

Jingcheng Zhang¹, Xingjian Zhou¹, Dong Shen¹, Qimeng Yu¹, Lin Yuan^2,*, Yingying Dong³

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 745-762, 2024, DOI:10.32604/phyton.2024.049734

Abstract As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv. oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result of the disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remote sensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutions offer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapid dispersal under suitable conditions, making it difficult to track the disease at… More >

Tsu-Yang Wu^1,2, Haonan Li², Saru Kumari³, Chien-Ming Chen^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 19-46, 2024, DOI:10.32604/cmc.2024.048347

Abstract Hyperspectral image classification stands as a pivotal task within the field of remote sensing, yet achieving high-precision classification remains a significant challenge. In response to this challenge, a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm (AFLA-SCNN) is proposed. The Adaptive Fick’s Law Algorithm (AFLA) constitutes a novel metaheuristic algorithm introduced herein, encompassing three new strategies: Adaptive weight factor, Gaussian mutation, and probability update policy. With adaptive weight factor, the algorithm can adjust the weights according to the change in the number of iterations to improve the performance of the algorithm. Gaussian… More >

JALPA V. CHOPDA, DHARMESH B. SANKHAVARA, JIGNESH P. PATEL, P. H. PARSANIA^*

Journal of Polymer Materials, Vol.38, No.1-2, pp. 35-48, 2021, DOI:10.32381/JPM.2021.38.1-2.4

Abstract Conventional curing study of epoxy resin of (2E, 6E)-bis (4-hydroxybenzylidene)-4-methyl cyclohexanone (EMBHBC) was conducted at 140 0 /150 0 C by using 4,4’-diaminodiphenylmethane (DDM),4,4’-diaminodiphenylsulphone (DDS),4-4’-diaminodiphenyl ether (DDE), p-phenylenediamine (PDA), 1,2,3,6-tetrahydrophthalic anhydride(THPA), maleic anhydride (MAH) and pyromellitic dianhydride (PMDA). The gel time for DDS, THPA and DDM hardeners are found considerably longer than those of DDE, PDA, MAH and PMDA systems indicated different reactivity towards curing of EMBHBC. Sol–gel analysis of cured resins was carried out in DMF at room temperature. Diamines cured samples showed 76.3-97.5% gel fractions, while anhydrides cured samples showed 84.6-99.6% gel fractions.… More >

Lujuan Deng, Ruochong Fu^*, Zuhe Li, Boyi Liu, Mengze Xue, Yuhao Cui

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4071-4089, 2024, DOI:10.32604/cmc.2024.048200

Abstract Multispectral pedestrian detection technology leverages infrared images to provide reliable information for visible light images, demonstrating significant advantages in low-light conditions and background occlusion scenarios. However, while continuously improving cross-modal feature extraction and fusion, ensuring the model’s detection speed is also a challenging issue. We have devised a deep learning network model for cross-modal pedestrian detection based on Resnet50, aiming to focus on more reliable features and enhance the model’s detection efficiency. This model employs a spatial attention mechanism to reweight the input visible light and infrared image data, enhancing the model’s focus on different More >

Usman Khan¹, Muhammad Khalid Khan¹, Muhammad Ayub Latif¹, Muhammad Naveed^1,2,*, Muhammad Mansoor Alam^2,3,4, Salman A. Khan¹, Mazliham Mohd Su’ud^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2967-3000, 2024, DOI:10.32604/cmc.2024.045101

Abstract Recently, there has been a notable surge of interest in scientific research regarding spectral images. The potential of these images to revolutionize the digital photography industry, like aerial photography through Unmanned Aerial Vehicles (UAVs), has captured considerable attention. One encouraging aspect is their combination with machine learning and deep learning algorithms, which have demonstrated remarkable outcomes in image classification. As a result of this powerful amalgamation, the adoption of spectral images has experienced exponential growth across various domains, with agriculture being one of the prominent beneficiaries. This paper presents an extensive survey encompassing multispectral and… More >

Ruochen Wang^1,#, Jianjun Dong^2,#, Lishan Jin³, Yuyan Sun³, Taogetao Baoyin², Xiumei Wang^*

Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 387-411, 2024, DOI:10.32604/phyton.2024.047573

Abstract Grassland biomass is an important parameter of grassland ecosystems. The complexity of the grassland canopy vegetation spectrum makes the long-term assessment of grassland growth a challenge. Few studies have explored the original spectral information of typical grasslands in Inner Mongolia and examined the influence of spectral information on aboveground biomass (AGB) estimation. In order to improve the accuracy of vegetation index inversion of grassland AGB, this study combined ground and Unmanned Aerial Vehicle (UAV) remote sensing technology and screened sensitive bands through ground hyperspectral data transformation and correlation analysis. The narrow band vegetation indices were… More >

Shi Qiu¹, Pengchang Zhang^1,*, Xingjia Tang², Zimu Zeng¹, Miao Zhang¹, Bingliang Hu^1,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3783-3800, 2023, DOI:10.32604/cmc.2023.042074

Abstract Sanxingdui cultural relics are the precious cultural heritage of humanity with high values of history, science, culture, art and research. However, mainstream analytical methods are contacting and detrimental, which is unfavorable to the protection of cultural relics. This paper improves the accuracy of the extraction, location, and analysis of artifacts using hyperspectral methods. To improve the accuracy of cultural relic mining, positioning, and analysis, the segmentation algorithm of Sanxingdui cultural relics based on the spatial spectrum integrated network is proposed with the support of hyperspectral techniques. Firstly, region stitching algorithm based on the relative position… More >