Rizwan Ali Naqvi¹, Dildar Hussain², Woong-Kee Loh^3,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 715-732, 2021, DOI:10.32604/cmc.2020.013249 - 30 October 2020

Abstract Multiple ocular region segmentation plays an important role in different applications such as biometrics, liveness detection, healthcare, and gaze estimation. Typically, segmentation techniques focus on a single region of the eye at a time. Despite the number of obvious advantages, very limited research has focused on multiple regions of the eye. Similarly, accurate segmentation of multiple eye regions is necessary in challenging scenarios involving blur, ghost effects low resolution, off-angles, and unusual glints. Currently, the available segmentation methods cannot address these constraints. In this paper, to address the accurate segmentation of multiple eye regions in… More >

Yuanyuan Liu^1,2, Shuo Zhang¹, Haiye Yu³, Yueyong Wang^4,*, Yuehan Feng¹, Jiahui Sun¹, Xiaokang Zhou¹

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 247-262, 2021, DOI:10.32604/cmc.2020.012328 - 30 October 2020

Abstract Intelligent straw coverage detection plays an important role in agricultural production and the ecological environment. Traditional pattern recognition has some problems, such as low precision and a long processing time, when segmenting complex farmland, which cannot meet the conditions of embedded equipment deployment. Based on these problems, we proposed a novel deep learning model with high accuracy, small model size and fast running speed named Residual Unet with Attention mechanism using depthwise convolution (RADw–UNet). This algorithm is based on the UNet symmetric codec model. All the feature extraction modules of the network adopt the residual… More >

Gauthier Fillières-Riveau¹ , Jean-Marie Favreau¹ , Vincent Barra¹ , Guillaume Touya²

Revue Internationale de Géomatique, Vol.30, No.1, pp. 105-126, 2020, DOI:10.3166/rig.2020.00104

Abstract Les cartes tactiles photoréalistes sont un des outils mobilisés par les personnes en situation de déficience visuelle pour appréhender leur environnement urbain proche, notamment dans le cadre de la mobilité, pour la traversée de carrefours par exemple. Ces cartes sont aujourd’hui principalement fabriquées artisanalement. Dans cet article, nous proposons une approche permettant de produire une segmentation sémantique d’une imagerie aérienne de précision, étape centrale de cette fabrication. Les différents éléments d’intérêt tels que trottoirs, passages piétons, ou îlots centraux sont ainsi localisés et tracés dans l’espace urbain. Nous présentons en particulier comment l’augmentation de cette More >

Meera Radhakrishnan^1,*, Anandan Panneerselvam², Nandhagopal Nachimuthu³

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1185-1199, 2020, DOI:10.32604/iasc.2020.012069 - 24 December 2020

Abstract Image segmentation is a crucial stage in the investigation of medical images and is predominantly implemented in various medical applications. In the case of investigating MRI brain images, the image segmentation is mainly employed to measure and visualize the anatomic structure of the brain that underwent modifications to delineate the regions. At present, distinct segmentation approaches with various degrees of accurateness and complexities are available. But, it needs tuning of various parameters to obtain optimal results. The tuning of parameters can be considered as an optimization issue using a similarity function in solution space. This… More >

Aziguli Wulamu^1,2,*, Jingyue Sang³, Dezheng Zhang^1,2, Zuxian Shi^1,2

Journal of New Media, Vol.2, No.4, pp. 149-155, 2020, DOI:10.32604/jnm.2020.014115 - 23 December 2020

Abstract Cultivated land extraction is essential for sustainable development and agriculture. In this paper, the network we propose is based on the encoderdecoder structure, which extracts the semantic segmentation neural network of cultivated land from satellite images and uses it for agricultural automation solutions. The encoder consists of two part: the first is the modified Xception, it can used as the feature extraction network, and the second is the atrous convolution, it can used to expand the receptive field and the context information to extract richer feature information. The decoder part uses the conventional upsampling operation More >

Ayyaz Hussain¹, Mohammed Alawairdhi², Fayez Alazemi³, Sajid Ali Khan⁴, Muhammad Ramzan^2,*

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 857-871, 2020, DOI:10.32604/iasc.2020.010120

Abstract The Computer Aided Diagnosis (CAD) systems are gaining more recognition and being used as an aid by clinicians for detection and interpretation of diseases every passing day due to their increasing accuracy and reliability. The lung(s) nodule detection is a very crucial and difficult step for CAD systems. In this paper, a hybrid approach for the lung nodule detection using a deformable model and distance transform has been proposed. The proposed method has the ability to detect all major kinds of nodules such as the juxta-plueral, isolated, and the juxta-vescular, along with the non-solid nodules More >

Wenting Qiao^1,2, Xiaoguang Wu^1,*, Wen Sun³, Qiande Wu^4,*

Structural Durability & Health Monitoring, Vol.14, No.4, pp. 355-374, 2020, DOI:10.32604/sdhm.2020.011479 - 04 December 2020

Abstract To solve the problem that the digital image recognition accuracy of concrete structure cracks is not high under the condition of uneven illumination and complex surface color of concrete structure, this paper has proposed a block segmentation method of maximum entropy threshold based on the digital image data obtained by the ACTIS automatic detection system. The steps in this research are as follows: 1. The crack digital images of concrete specimens with typical features were collected by using the Actis system of KURABO Co., Ltd., of Japan in the concrete beam bending test. 2. The… More >

Jiajie Mai¹, Xuemiao Xu^2,*, Guorong Xiao³, Zijun Deng², Jiaxing Chen²

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 847-855, 2020, DOI:10.32604/iasc.2020.010119

Abstract The Salient object detection aims to segment out the most visually distinctive objects in an image, which is a challenging task in computer vision. In this paper, we present the PGCA-Net equipped with the pyramid guided channel attention fusion block (PGCAFB) for the saliency detection task. Given an input image, the hierarchical features are extracted using a deep convolutional neural network (DCNN), then starting from the highest-level semantic features, we stage-by-stage restore the spatial saliency details by aggregating the lowerlevel detailed features. Since for the weak discriminative ability of the shallow detailed features, directly introducing More >

Eslam Mohammed Abdelkader^1,2,*, Osama Moselhi³, Mohamed Marzouk⁴, Tarek Zayed⁵

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 643-661, 2020, DOI:10.32604/iasc.2020.010100

Abstract Image segmentation is one of the fundamental stages in computer vision applications. Several meta-heuristics have been applied to solve the segmentation problems by extending the Otsu and entropy functions. However, no single-objective function can optimally handle the diversity of information in images besides the multimodality issues of gray-level images. This paper presents a self-adaptive multi-objective optimization-based method for the detection of crack images in reinforced concrete bridges. The proposed method combines the flexibility of information theory functions in addition to the invasive weed optimization algorithm for bi-level thresholding. The capabilities of the proposed method are More >

Guangli Zhu, Wenting Liu, Shunxiang Zhang^*, Xiang Chen , Chang Yin

Computer Systems Science and Engineering, Vol.35, No.3, pp. 223-232, 2020, DOI:10.32604/csse.2020.35.223

Abstract The current method of extracting new login sentiment words not only ignores the diversity of patterns constituted by new multi-character words (the number of words is greater than two), but also disregards the influence of other new words co-occurring with a new word connoting sentiment. To solve this problem, this paper proposes a method for extracting new login sentiment words from Chinese micro-blog based on improved mutual information. First, micro-blog data are preprocessed, taking into consideration some nonsense signals such as web links and punctuation. Based on preprocessed data, the candidate strings are obtained by… More >