Fayaz Muhammad¹, Jahangir Khan¹, Asad Ullah¹, Fasee Ullah¹, Razaullah Khan², Inayat Khan², Mohammed ElAffendi³, Gauhar Ali^3,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 647-664, 2023, DOI:10.32604/cmc.2023.038748

Abstract IIF (Indirect Immune Florescence) has gained much attention recently due to its importance in medical sciences. The primary purpose of this work is to highlight a step-by-step methodology for detecting autoimmune diseases. The use of IIF for detecting autoimmune diseases is widespread in different medical areas. Nearly 80 different types of autoimmune diseases have existed in various body parts. The IIF has been used for image classification in both ways, manually and by using the Computer-Aided Detection (CAD) system. The data scientists conducted various research works using an automatic CAD system with low accuracy. The diseases in the human body… More >

Yixin Tang^*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 867-891, 2023, DOI:10.32604/cmc.2023.041550

Abstract Cartoons serve as significant sources of entertainment for children and adolescents. However, numerous animated videos contain unsuitable content, such as violence, eroticism, abuse, and vehicular accidents. Current content detection methods rely on manual inspection, which is resource-intensive, time-consuming, and not always reliable. Therefore, more efficient detection methods are necessary to safeguard young viewers. This paper addresses this significant problem by proposing a novel deep learning-based system, AnimeNet, designed to detect varying degrees of violent and erotic content in videos. AnimeNet utilizes a novel Convolutional Neural Network (CNN) model to extract image features effectively, classifying violent and erotic scenes in videos… More >

Asifa Mehmood Qureshi¹, Nouf Abdullah Almujally², Saud S. Alotaibi³, Mohammed Hamad Alatiyyah⁴, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3707-3725, 2023, DOI:10.32604/cmc.2023.040738

Abstract Road congestion, air pollution, and accident rates have all increased as a result of rising traffic density and worldwide population growth. Over the past ten years, the total number of automobiles has increased significantly over the world. In this paper, a novel method for intelligent traffic surveillance is presented. The proposed model is based on multilabel semantic segmentation using a random forest classifier which classifies the images into five classes. To improve the results, mean-shift clustering was applied to the segmented images. Afterward, the pixels given the label for the vehicle were extracted and blob detection was applied to mark… More >

Shaohua Li, Haixiang Zhang^*, Hanjie Ma, Jie Feng, Mingfeng Jiang

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3379-3392, 2023, DOI:10.32604/cmc.2023.041538

Abstract Scale variation is a major challenge in multi-person pose estimation. In scenes where persons are present at various distances, models tend to perform better on larger-scale persons, while the performance for smaller-scale persons often falls short of expectations. Therefore, effectively balancing the persons of different scales poses a significant challenge. So this paper proposes a new multi-person pose estimation model called FSA Net to improve the model’s performance in complex scenes. Our model utilizes High-Resolution Network (HRNet) as the backbone and feeds the outputs of the last stage’s four branches into the DCB module. The dilated convolution-based (DCB) module employs… More >

B. Keerthi Samhitha^*, R. Subhashini

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3125-3142, 2023, DOI:10.32604/iasc.2023.040643

Abstract Accurate and rapid detection of fish behaviors is critical to perceive health and welfare by allowing farmers to make informed management decisions about recirculating the aquaculture system while decreasing labor. The classic detection approach involves placing sensors on the skin or body of the fish, which may interfere with typical behavior and welfare. The progress of deep learning and computer vision technologies opens up new opportunities to understand the biological basis of this behavior and precisely quantify behaviors that contribute to achieving accurate management in precision farming and higher production efficacy. This study develops an intelligent fish behavior classification using… More >

Eugene Tan Boon Hong¹, Yung-Wey Chong^1,*, Tat-Chee Wan¹, Kok-Lim Alvin Yau²

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2337-2354, 2023, DOI:10.32604/cmc.2023.038695

Abstract The existing dataset for visual dialog comprises multiple rounds of questions and a diverse range of image contents. However, it faces challenges in overcoming visual semantic limitations, particularly in obtaining sufficient context from visual and textual aspects of images. This paper proposes a new visual dialog dataset called Diverse History-Dialog (DS-Dialog) to address the visual semantic limitations faced by the existing dataset. DS-Dialog groups relevant histories based on their respective Microsoft Common Objects in Context (MSCOCO) image categories and consolidates them for each image. Specifically, each MSCOCO image category consists of top relevant histories extracted based on their semantic relationships… More >

Anas Bilal^1,*, Xiaowen Liu¹, Haixia Long^1,*, Muhammad Shafiq², Muhammad Waqar³

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2401-2426, 2023, DOI:10.32604/cmc.2023.037857

Abstract Farming is cultivating the soil, producing crops, and keeping livestock. The agricultural sector plays a crucial role in a country’s economic growth. This research proposes a two-stage machine learning framework for agriculture to improve efficiency and increase crop yield. In the first stage, machine learning algorithms generate data for extensive and far-flung agricultural areas and forecast crops. The recommended crops are based on various factors such as weather conditions, soil analysis, and the amount of fertilizers and pesticides required. In the second stage, a transfer learning-based model for plant seedlings, pests, and plant leaf disease datasets is used to detect… More >

Amit V. Patel¹, Arpan Desai¹, Issa Elfergani^2,3,*, Hiren Mewada⁴, Chemseddine Zebiri⁵, Keyur Mahant¹, Jonathan Rodriguez², Raed Abd-Alhameed³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2867-2879, 2023, DOI:10.32604/cmes.2023.026200

Abstract A four-element compact dual-band patch antenna having a common ground plane operating at 28/38 GHz is proposed for millimeter-wave communication systems in this paper. The multiple-input-multiple-output (MIMO) antenna geometry consists of a slotted ellipse enclosed within a hollow circle which is orthogonally rotated with a connected partial ground at the back. The overall size of the four elements MIMO antenna is 2.24λ × 2.24λ (at 27.12 GHz). The prototype of four-element MIMO resonator is designed and printed using Rogers RT Duroid 5880 with ε_r = 2.2 and loss tangent = 0.0009 and having a thickness of 0.8 mm. It covers… More >

Mohd Anul Haq^1,*, Siwar Ben Hadj Hassine², Sharaf J. Malebary³, Hakeem A. Othman⁴, Elsayed M. Tag-Eldin⁵

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2689-2705, 2023, DOI:10.32604/csse.2023.039904

Abstract Hyperspectral images can easily discriminate different materials due to their fine spectral resolution. However, obtaining a hyperspectral image (HSI) with a high spatial resolution is still a challenge as we are limited by the high computing requirements. The spatial resolution of HSI can be enhanced by utilizing Deep Learning (DL) based Super-resolution (SR). A 3D-CNNHSR model is developed in the present investigation for 3D spatial super-resolution for HSI, without losing the spectral content. The 3D-CNNHSR model was tested for the Hyperion HSI. The pre-processing of the HSI was done before applying the SR model so that the full advantage of… More >

Ghoroub Talal Bostaji^*, Emad Sami Jaha

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1571-1591, 2023, DOI:10.32604/csse.2023.039701

Abstract Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy issues. Therefore, biometric systems have emerged as a technology with the capability to identify or authenticate individuals based on their physiological and behavioral characteristics. Among different viable biometric modalities, the human ear structure can offer unique and valuable discriminative characteristics for human recognition systems. In recent years, most existing traditional ear recognition systems have been designed based on computer vision models and have achieved successful results. Nevertheless, such traditional models can be sensitive to several unconstrained… More >