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  • Open Access

    ARTICLE

    Deep-Net: Fine-Tuned Deep Neural Network Multi-Features Fusion for Brain Tumor Recognition

    Muhammad Attique Khan1,2, Reham R. Mostafa3, Yu-Dong Zhang2, Jamel Baili4, Majed Alhaisoni5, Usman Tariq6, Junaid Ali Khan1, Ye Jin Kim7, Jaehyuk Cha7,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3029-3047, 2023, DOI:10.32604/cmc.2023.038838

    Abstract Manual diagnosis of brain tumors using magnetic resonance images (MRI) is a hectic process and time-consuming. Also, it always requires an expert person for the diagnosis. Therefore, many computer-controlled methods for diagnosing and classifying brain tumors have been introduced in the literature. This paper proposes a novel multimodal brain tumor classification framework based on two-way deep learning feature extraction and a hybrid feature optimization algorithm. NasNet-Mobile, a pre-trained deep learning model, has been fine-tuned and two-way trained on original and enhanced MRI images. The haze-convolutional neural network (haze-CNN) approach is developed and employed on the original images for contrast enhancement.… More >

  • Open Access

    ARTICLE

    Optical and Mechanical Properties of Ramie Fiber/Epoxy Resin Transparent Composites

    Chunhua Liu1, Dongfang Zou1, Qinqin Huang1, Shang Li2, Xia Zheng1, Xingong Li1,*

    Journal of Renewable Materials, Vol.11, No.10, pp. 3613-3624, 2023, DOI:10.32604/jrm.2023.028111

    Abstract The residual resources of ramie fiber-based textile products were used as raw materials. Ramie fiber felt (RF) was modified by NaClO2 aqueous solution and then impregnated with water-based epoxy resin (WER). RF/WER transparent composite materials were prepared by lamination hot pressing process. The composite materials’color difference, transmittance, haze, density, water absorption, and mechanical properties were determined to assess the effects of NaClO2 treatment and the number of ramie fiber layers on the properties of the prepared composites. The results showed significantly improved optical and mechanical properties of the RF/WER transparent composites after NaClO2 treatment. With the increase of ramie fiber… More > Graphic Abstract

    Optical and Mechanical Properties of Ramie Fiber/Epoxy Resin Transparent Composites

  • Open Access

    ARTICLE

    Identification of a new Hazelnut disease in Liaoning Province: Hazelnut husk brown rot

    JUN SUN1,*, MING XIE1, JIACHEN HAO1, NAN MAO1, LIJING CHEN2,*, YUANYUAN QIN3

    BIOCELL, Vol.46, No.9, pp. 2145-2149, 2022, DOI:10.32604/biocell.2022.020500

    Abstract Hazelnut husk brown rot has been identified as a new disease in Liaoning Province in recent years. The objective of this study as to identify the pathogen. [Method] In this study, a standard sample of hazelnut husk brown rot was collected from Songmudao Base in Dalian City, Liaoning Province. The pathogen was identified by the studies of the morphology, pathogenicity, and analyses of ITS and LSU sequences. The pathogen was isolated and purified, which was confirmed by Koch’s postulates. The symptoms after inoculation were the same as those collected directly from a diseased tree, which showed that it was the… More >

  • Open Access

    ARTICLE

    Dark and Bright Channel Priors for Haze Removal in Day and Night Images

    U. Hari, A. Ruhan Bevi*

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 957-967, 2022, DOI:10.32604/iasc.2022.023605

    Abstract Removal of noise from images is very important as a clear, denoised image is essential for any application. In this article, a modified haze removal algorithm is developed by applying combined dark channel prior and multi-scale retinex theory. The combined dark channel prior (DCP) and bright channel prior (BCP) together with the multi-scale retinex (MSR) algorithm is used to dynamically optimize the transmission map and thereby improve visibility. The proposed algorithm performs effective denoising of images considering the properties of retinex theory. The proposed method removes haze on an image scene through estimation of the atmospheric light and manipulating the… More >

  • Open Access

    ARTICLE

    FPD Net: Feature Pyramid DehazeNet

    Shengchun Wang1, Peiqi Chen1, Jingui Huang1,*, Tsz Ho Wong2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1167-1181, 2022, DOI:10.32604/csse.2022.018911

    Abstract We propose an end-to-end dehazing model based on deep learning (CNN network) and uses the dehazing model re-proposed by AOD-Net based on the atmospheric scattering model for dehazing. Compare to the previously proposed dehazing network, the dehazing model proposed in this paper make use of the FPN network structure in the field of target detection, and uses five feature maps of different sizes to better obtain features of different proportions and different sub-regions. A large amount of experimental data proves that the dehazing model proposed in this paper is superior to previous dehazing technologies in terms of PSNR, SSIM, and… More >

  • Open Access

    ARTICLE

    Multiscale Image Dehazing and Restoration: An Application for Visual Surveillance

    Samia Riaz1, Muhammad Waqas Anwar2, Irfan Riaz3, Hyun-Woo Kim4, Yunyoung Nam4,*, Muhammad Attique Khan5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1-17, 2022, DOI:10.32604/cmc.2022.018268

    Abstract The captured outdoor images and videos may appear blurred due to haze, fog, and bad weather conditions. Water droplets or dust particles in the atmosphere cause the light to scatter, resulting in very limited scene discernibility and deterioration in the quality of the image captured. Currently, image dehazing has gained much popularity because of its usability in a wide variety of applications. Various algorithms have been proposed to solve this ill-posed problem. These algorithms provide quite promising results in some cases, but they include undesirable artifacts and noise in haze patches in adverse cases. Some of these techniques take unrealistic… More >

  • Open Access

    RETRACTION

    Deep-Learning-Empowered 3D Reconstruction for Dehazed Images in IoTEnhanced Smart Cities

    Jing Zhang1,2, Xin Qi3,*, San Hlaing Myint3, Zheng Wen4

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2809-2809, 2021, DOI:10.32604/cmc.2021.17410

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Deep-Learning-Empowered 3D Reconstruction for Dehazed Images in IoT-Enhanced Smart Cities

    Jing Zhang1,2, Xin Qi3,*, San Hlaing Myint3, Zheng Wen4

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2807-2824, 2021, DOI:10.32604/cmc.2021.017410

    Abstract With increasingly more smart cameras deployed in infrastructure and commercial buildings, 3D reconstruction can quickly obtain cities’ information and improve the efficiency of government services. Images collected in outdoor hazy environments are prone to color distortion and low contrast; thus, the desired visual effect cannot be achieved and the difficulty of target detection is increased. Artificial intelligence (AI) solutions provide great help for dehazy images, which can automatically identify patterns or monitor the environment. Therefore, we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning. First, we propose a fine transmission image deep convolutional… More >

  • Open Access

    ARTICLE

    Characterization of Extracts from the Bark of the Gabon Hazel Tree (Coula edulis baill) for Antioxidant, Antifungal and Anti-termite Products

    Christ Stone Arnaud Bopenga Bopenga1, Henri Meyo Degboevi1, Kevin Candelier2, Prosper Edou Engonga3, Stéphane Dumarçay1, Marie France Thévenon2, Christine Gérardin Charbonnier1, Philippe Gérardin1,*

    Journal of Renewable Materials, Vol.9, No.1, pp. 17-33, 2021, DOI:10.32604/jrm.2021.013366

    Abstract

    Chemical composition of the bark extracts of Coula edulis was investigated to find potential antioxidant, anti-termite and antifungal compounds which can find useful applications in the fields of food, nutraceuticals, cosmetics or agrochemical. Phytochemical screening revealed the presence of several groups of active molecules such as alkaloids, polyphenols, flavonoids, saponins and sterols and/or terpenes in the different extracts. Total phenols, condensed tannins and flavonoids contents corroborated phytochemical screening. Gas chromatography-mass spectrometry (GC-MS) analysis revealed compounds in dichloromethane extract different from those obtained with all the other solvents. Hexadecanoic and trans-9-octadecenoic acids, as well as stigmasterol and β-sitosterol have been identified… More >

  • Open Access

    ARTICLE

    A Study of Single Image Haze Removal Using a Novel White-Patch RetinexBased Improved Dark Channel Prior Algorithm

    Yao-Liang Chung1,*, Hung-Yuan Chung2, Yu-Shan Chen2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 367-383, 2020, DOI:10.31209/2020.100000206

    Abstract In this study, we introduce an algorithm which is based on a series of wellknown algorithms and mainly uses an improved dark channel prior algorithm and the White-Patch Retinex algorithm (both are heterogeneous algorithms) in order to effectively remove the haze from a single image. When used in conjunction with a heterogeneous architecture, the value of the algorithm becomes even greater. With an effective design and a novel procedure, the proposed algorithm can not only restore a clear image, but also solve the halo effect, color distortion, and long operating time issues resulting from the dark channel prior. Rich experimental… More >

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