Wen-Tsai Sung¹, Indra Griha Tofik Isa^2,3, Sung-Jung Hsiao^4,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-31, 2026, DOI:10.32604/cmc.2025.070922 - 09 December 2025

Abstract Mango is a plant with high economic value in the agricultural industry; thus, it is necessary to maximize the productivity performance of the mango plant, which can be done by implementing artificial intelligence. In this study, a lightweight object detection model will be developed that can detect mango plant conditions based on disease potential, so that it becomes an early detection warning system that has an impact on increasing agricultural productivity. The proposed lightweight model integrates YOLOv7-Tiny and the proposed modules, namely the C2S module. The C2S module consists of three sub-modules such as the… More >

Baishun Zhou^1,2, Haijiao Zhao³, Yuxin Wen², Gangyi Ding¹, Ying Xing^3,*, Xinyang Lin⁴, Lei Xiao⁵

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5201-5221, 2025, DOI:10.32604/cmc.2025.065726 - 30 July 2025

Abstract In recent years, with the rapid development of software systems, the continuous expansion of software scale and the increasing complexity of systems have led to the emergence of a growing number of software metrics. Defect prediction methods based on software metric elements highly rely on software metric data. However, redundant software metric data is not conducive to efficient defect prediction, posing severe challenges to current software defect prediction tasks. To address these issues, this paper focuses on the rational clustering of software metric data. Firstly, multiple software projects are evaluated to determine the preset number… More >

Sarah M. Kamel^1,*, Mai A. Fadel², Lamiaa Elrefaei^1,3, Shimaa I. Hassan^1,4

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 373-411, 2025, DOI:10.32604/cmes.2025.062837 - 11 April 2025

Abstract Visual question answering (VQA) is a multimodal task, involving a deep understanding of the image scene and the question’s meaning and capturing the relevant correlations between both modalities to infer the appropriate answer. In this paper, we propose a VQA system intended to answer yes/no questions about real-world images, in Arabic. To support a robust VQA system, we work in two directions: (1) Using deep neural networks to semantically represent the given image and question in a fine-grained manner, namely ResNet-152 and Gated Recurrent Units (GRU). (2) Studying the role of the utilized multimodal bilinear… More >

Abdul Sattar Palli^1,6,*, Jafreezal Jaafar^1,2, Manzoor Ahmed Hashmani^1,3, Heitor Murilo Gomes^4,5, Aeshah Alsughayyir⁷, Abdul Rehman Gilal¹

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1827-1845, 2023, DOI:10.32604/cmc.2023.033934 - 06 February 2023

Abstract Every application in a smart city environment like the smart grid, health monitoring, security, and surveillance generates non-stationary data streams. Due to such nature, the statistical properties of data changes over time, leading to class imbalance and concept drift issues. Both these issues cause model performance degradation. Most of the current work has been focused on developing an ensemble strategy by training a new classifier on the latest data to resolve the issue. These techniques suffer while training the new classifier if the data is imbalanced. Also, the class imbalance ratio may change greatly from… More >

Md. Saiful Islam, Shuvo Jyoti Das, Md. Riajul Alam Khan, Sifat Momen^*, Nabeel Mohammed

Computer Systems Science and Engineering, Vol.44, No.1, pp. 519-534, 2023, DOI:10.32604/csse.2023.025282 - 01 June 2022

Abstract COVID-19 has created a panic all around the globe. It is a contagious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), originated from Wuhan in December 2019 and spread quickly all over the world. The healthcare sector of the world is facing great challenges tackling COVID cases. One of the problems many have witnessed is the misdiagnosis of COVID-19 cases with that of healthy and pneumonia cases. In this article, we propose a deep Convolutional Neural Network (CNN) based approach to detect COVID+ (i.e., patients with COVID-19), pneumonia and normal cases, from the… More >