Yung-Hsiang Hung, Chuen-Kai Fan, Wen-Pai Wang^*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2323-2349, 2025, DOI:10.32604/cmc.2025.063270 - 16 April 2025

Abstract Bees play a crucial role in the global food chain, pollinating over 75% of food and producing valuable products such as bee pollen, propolis, and royal jelly. However, the Asian hornet poses a serious threat to bee populations by preying on them and disrupting agricultural ecosystems. To address this issue, this study developed a modified YOLOv7tiny (You Only Look Once) model for efficient hornet detection. The model incorporated space-to-depth (SPD) and squeeze-and-excitation (SE) attention mechanisms and involved detailed annotation of the hornet’s head and full body, significantly enhancing the detection of small objects. The Taguchi… More >

Xinyi Wang^*, Wanru Song, Chuanyan Hao, Feng Liu

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3351-3368, 2025, DOI:10.32604/cmc.2025.062922 - 16 April 2025

Abstract As Deepfake technology continues to evolve, the distinction between real and fake content becomes increasingly blurred. Most existing Deepfake video detection methods rely on single-frame facial image features, which limits their ability to capture temporal differences between frames. Current methods also exhibit limited generalization capabilities, struggling to detect content generated by unknown forgery algorithms. Moreover, the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content (AIGC) present significant challenges for traditional detection frameworks, which must balance high detection accuracy with robust performance. To address these challenges, we propose a novel Deepfake detection… More >

Poonam Sharma¹, Bhisham Sharma^2,*, Dhirendra Prasad Yadav³, Surbhi Bhatia Khan^4,5,6,*, Ahlam Almusharraf⁷

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3227-3245, 2025, DOI:10.32604/cmc.2025.062376 - 16 April 2025

Abstract Rapid and precise diagnostic tools for Monkeypox (Mpox) lesions are crucial for effective treatment because their symptoms are similar to those of other pox-related illnesses, like smallpox and chickenpox. The morphological similarities between smallpox, chickenpox, and monkeypox, particularly in how they appear as rashes and skin lesions, which can sometimes make diagnosis challenging. Chickenpox lesions appear in many simultaneous phases and are more diffuse, often beginning on the trunk. In contrast, monkeypox lesions emerge progressively and are typically centralized on the face, palms, and soles. To provide accessible diagnostics, this study introduces a novel method… More >

Omar Alqahtani, Mohamed Ghouse^*, Asfia Sabahath, Omer Bin Hussain, Arshiya Begum

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2221-2244, 2025, DOI:10.32604/cmc.2025.061977 - 16 April 2025

Abstract This paper introduces a novel method for medical image retrieval and classification by integrating a multi-scale encoding mechanism with Vision Transformer (ViT) architectures and a dynamic multi-loss function. The multi-scale encoding significantly enhances the model’s ability to capture both fine-grained and global features, while the dynamic loss function adapts during training to optimize classification accuracy and retrieval performance. Our approach was evaluated on the ISIC-2018 and ChestX-ray14 datasets, yielding notable improvements. Specifically, on the ISIC-2018 dataset, our method achieves an F1-Score improvement of +4.84% compared to the standard ViT, with a precision increase of +5.46% More >

Meng Zhu^1,2, Xingyue Wang³, Honge Ren^3,4,*, Abeer Hakeem⁵, Linda Mohaisen^5,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2889-2905, 2025, DOI:10.32604/cmc.2025.061421 - 16 April 2025

Abstract Changing a person’s posture and low resolution are the key challenges for person re-identification (ReID) in various deep learning applications. In this paper, we introduce an innovative architecture using a dual attention network that includes an attention module and a joint measurement module of spatial-temporal information. The proposed approach can be classified into two main tasks. Firstly, the spatial attention feature map is formed by aggregating features in the spatial dimension. Additionally, the same operation is carried out on the channel dimension to form channel attention feature maps. Therefore, the receptive field size is adjusted… More >

Wenhai Zhao¹, Wanrun Li^1,2,*, Ximei Li^1,2, Shoutu Li³, Yongfeng Du^1,2

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 593-611, 2025, DOI:10.32604/sdhm.2024.057759 - 03 April 2025

Abstract Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies, as well as the inability to achieve precise full-field monitoring, this paper proposes a method for identifying the structural dynamic characteristics of wind turbines based on visual monitoring data fusion. Firstly, the Lucas-Kanade Tomasi (LKT) optical flow method and a multi-region of interest (ROI) monitoring structure are employed to track pixel displacements, which are subsequently subjected to band pass filtering and resampling operations. Secondly, the actual displacement time history is derived through double integration of the acquired acceleration data and… More >

Antonio Rodrigues da Cunha Neto¹, Alexandra dos Santos Ambrósio¹, Arlinda de Jesus Rodrigues Resende¹, Breno Régis Santos¹, Michele Carla Nadal^2,*

Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 539-560, 2025, DOI:10.32604/phyton.2025.061776 - 31 March 2025

Abstract Cytokinins are plant hormones that are essential for plant growth and development and are involved in a variety of processes. They are synthesized by the modification of adenine with an isoprenoid chain, resulting in cytokinins such as isopentenyladenine and zeatin. The levels of these hormones are regulated by conjugation, degradation and oxidation processes that modulate their activity. Cytokinins are perceived by cells through specific receptors that, when activated, trigger signaling cascades responsible for regulating the expression of genes critical for development. In addition, cytokinins interact with other hormones, such as auxins, to coordinate plant growth… More >

Nathan Isaac Dibal^1,*, Martha Orendu Oche Attah^1,2

BIOCELL, Vol.49, No.3, pp. 419-435, 2025, DOI:10.32604/biocell.2025.060565 - 31 March 2025

Abstract Oxidative stress is characterized by elevated intracellular reactive oxygen species (ROS) levels. At physiological levels, ROS work as signaling molecules, helping cells go through the cell cycle normally and keeping their balance. They also balance several physiological processes. However, a shift in the delicate balance between antioxidants and ROS results in aberrant cell death and deleterious effects. Elevated ROS is implicated in many diseases and disorders like diabetes, autoimmune diseases, infertility, and cardiovascular disorders. The imbalance disrupts normal cellular functions, including cell division. ROS are important regulators of the cell cycle, exerting both favorable and More >

Zaid Derea^1,2,*, Beiji Zou¹, Xiaoyan Kui^1,*, Monir Abdullah³, Alaa Thobhani¹, Amr Abdussalam⁴

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 115-136, 2025, DOI:10.32604/cmc.2025.062729 - 26 March 2025

Abstract Improving website security to prevent malicious online activities is crucial, and CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) has emerged as a key strategy for distinguishing human users from automated bots. Text-based CAPTCHAs, designed to be easily decipherable by humans yet challenging for machines, are a common form of this verification. However, advancements in deep learning have facilitated the creation of models adept at recognizing these text-based CAPTCHAs with surprising efficiency. In our comprehensive investigation into CAPTCHA recognition, we have tailored the renowned UpDown image captioning model specifically for this… More >

Faten S. Alamri¹, Tariq Sadad^2,*, Ahmed S. Almasoud³, Raja Atif Aurangzeb⁴, Amjad Khan³

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1023-1039, 2025, DOI:10.32604/cmc.2025.061890 - 26 March 2025

Abstract Mango farming significantly contributes to the economy, particularly in developing countries. However, mango trees are susceptible to various diseases caused by fungi, viruses, and bacteria, and diagnosing these diseases at an early stage is crucial to prevent their spread, which can lead to substantial losses. The development of deep learning models for detecting crop diseases is an active area of research in smart agriculture. This study focuses on mango plant diseases and employs the ConvNeXt and Vision Transformer (ViT) architectures. Two datasets were used. The first, MangoLeafBD, contains data for mango leaf diseases such as… More >