Sobia Nawaz¹, Sidra Rasheed², Wania Sami³, Lal Hussain^4,5,*, Amjad Aldweesh^6,*, Elsayed Tag eldin⁷, Umair Ahmad Salaria^8,9, Mohammad Shahbaz Khan¹⁰

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5213-5228, 2023, DOI:10.32604/cmc.2023.037543

Abstract This study is designed to develop Artificial Intelligence (AI) based analysis tool that could accurately detect COVID-19 lung infections based on portable chest x-rays (CXRs). The frontline physicians and radiologists suffer from grand challenges for COVID-19 pandemic due to the suboptimal image quality and the large volume of CXRs. In this study, AI-based analysis tools were developed that can precisely classify COVID-19 lung infection. Publicly available datasets of COVID-19 (N = 1525), non-COVID-19 normal (N = 1525), viral pneumonia (N = 1342) and bacterial pneumonia (N = 2521) from the Italian Society of Medical and Interventional Radiology (SIRM), Radiopaedia, The… More >

Hiam Alquran^1,2, Yazan Al-Issa³, Mohammed Alslatie⁴, Isam Abu-Qasmieh¹, Amin Alqudah³, Wan Azani Mustafa^5,7,*, Yasmin Mohd Yacob^6,7

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1653-1671, 2023, DOI:10.32604/csse.2023.033861

Abstract Liver cancer is the second leading cause of cancer death worldwide. Early tumor detection may help identify suitable treatment and increase the survival rate. Medical imaging is a non-invasive tool that can help uncover abnormalities in human organs. Magnetic Resonance Imaging (MRI), in particular, uses magnetic fields and radio waves to differentiate internal human organs tissue. However, the interpretation of medical images requires the subjective expertise of a radiologist and oncologist. Thus, building an automated diagnosis computer-based system can help specialists reduce incorrect diagnoses. This paper proposes a hybrid automated system to compare the performance of 3D features and 2D… More >

Man-Ting Li, Sang-Hyun Lee^*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6155-6165, 2022, DOI:10.32604/cmc.2022.025714

Abstract This study aims to detect and prevent greening disease in citrus trees using a deep neural network. The process of collecting data on citrus greening disease is very difficult because the vector pests are too small. In this paper, since the amount of data collected for deep learning is insufficient, we intend to use the efficient feature extraction function of the neural network based on the Transformer algorithm. We want to use the Cascade Region-based Convolutional Neural Networks (Cascade R-CNN) Swin model, which is a mixture of the transformer model and Cascade R-CNN model to detect greening disease occurring in… More >

Hiam Alquran^1,2, Wan Azani Mustafa^3,4,*, Isam Abu Qasmieh², Yasmeen Mohd Yacob^3,4, Mohammed Alsalatie⁵, Yazan Al-Issa⁶, Ali Mohammad Alqudah²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5117-5134, 2022, DOI:10.32604/cmc.2022.025692

Abstract Cervical cancer is screened by pap smear methodology for detection and classification purposes. Pap smear images of the cervical region are employed to detect and classify the abnormality of cervical tissues. In this paper, we proposed the first system that it ables to classify the pap smear images into a seven classes problem. Pap smear images are exploited to design a computer-aided diagnoses system to classify the abnormality in cervical images cells. Automated features that have been extracted using ResNet101 are employed to discriminate seven classes of images in Support Vector Machine (SVM) classifier. The success of this proposed system… More >

Chao Zhu¹, Yike Wang¹, Dongbing Pu¹,Miao Qi^1,*, Hui Sun^2,*, Lei Tan^3,*

Journal on Big Data, Vol.2, No.3, pp. 95-104, 2020, DOI:10.32604/jbd.2020.010431

Abstract Nowadays, action recognition is widely applied in many fields. However, action is hard to define by single modality information. The difference between image recognition and action recognition is that action recognition needs more modality information to depict one action, such as the appearance, the motion and the dynamic information. Due to the state of action evolves with the change of time, motion information must be considered when representing an action. Most of current methods define an action by spatial information and motion information. There are two key elements of current action recognition methods: spatial information achieved by sampling sparsely on… More >

Guanghui Yu¹, Honghui Fan¹, Hongyan Zhou¹, Tao Wu¹, Hongjin Zhu^{1, *}

Journal on Artificial Intelligence, Vol.2, No.3, pp. 125-135, 2020, DOI:10.32604/jai.2020.010501

Abstract When we use traditional computer vision Inspection technology to locate the vehicles, we find that the results were unsatisfactory, because of the existence of diversified scenes and uncertainty. So, we present a new method based on improved SSD model. We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model. Meanwhile, the new method optimizes the loss function, such as the loss function of predicted offset, and makes the loss function drop more smoothly near zero points. In addition, the new method improves cross entropy loss function of category prediction,… More >