Muhammad Hameed Siddiqi^1,*, Asfandyar Khan², Muhammad Bilal Khan², Abdullah Khan², Madallah Alruwaili¹, Saad Alanazi¹

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2219-2239, 2023, DOI:10.32604/csse.2023.040212

Abstract The use of the internet is increasing all over the world on a daily basis in the last two decades. The increase in the internet causes many sexual crimes, such as sexual misuse, domestic violence, and child pornography. Various research has been done for pornographic image detection and classification. Most of the used models used machine learning techniques and deep learning models which show less accuracy, while the deep learning model ware used for classification and detection performed better as compared to machine learning. Therefore, this research evaluates the performance analysis of intelligent neural-based deep learning models which are based… More >

Aiping Xu^1,2, Xuan Zou³, Chao Wang^2,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1043-1059, 2023, DOI:10.32604/csse.2023.039645

Abstract To protect the environment, the discharged sewage’s quality must meet the state’s discharge standards. There are many water quality indicators, and the pH (Potential of Hydrogen) value is one of them. The natural water’s pH value is 6.0–8.5. The sewage treatment plant uses some data in the sewage treatment process to monitor and predict whether wastewater’s pH value will exceed the standard. This paper aims to study the deep learning prediction model of wastewater’s pH. Firstly, the research uses the random forest method to select the data features and then, based on the sliding window, convert the data set into… More >

K. Ravishankar^*, C. Jothikumar

Computer Systems Science and Engineering, Vol.47, No.1, pp. 613-635, 2023, DOI:10.32604/csse.2023.038343

Abstract Since COVID-19 infections are increasing all over the world, there is a need for developing solutions for its early and accurate diagnosis is a must. Detection methods for COVID-19 include screening methods like Chest X-rays and Computed Tomography (CT) scans. More work must be done on preprocessing the datasets, such as eliminating the diaphragm portions, enhancing the image intensity, and minimizing noise. In addition to the detection of COVID-19, the severity of the infection needs to be estimated. The HSDC model is proposed to solve these problems, which will detect and classify the severity of COVID-19 from X-ray and CT-scan… More >

Arfat Ahmad Khan¹, Malik Muhammad Ali Shahid², Rab Nawaz Bashir², Salman Iqbal², Arshad Shehzad Ahmad Shahid³, Javeria Maqbool⁴, Chitapong Wechtaisong^5,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3743-3761, 2023, DOI:10.32604/cmc.2023.033924

Abstract COVID-19 disease caused by the SARS-CoV-2 virus has created social and economic disruption across the world. The ability of the COVID-19 virus to quickly mutate and transfer has created serious concerns across the world. It is essential to detect COVID-19 infection caused by different variants to take preventive measures accordingly. The existing method of detection of infections caused by COVID-19 and its variants is costly and time-consuming. The impacts of the COVID-19 pandemic in developing countries are very drastic due to the unavailability of medical facilities and infrastructure to handle the pandemic. Pneumonia is the major symptom of COVID-19 infection.… More >

Abu Saleh Musa Miah¹, Jungpil Shin^1,*, Md. Al Mehedi Hasan¹, Md Abdur Rahim², Yuichi Okuyama¹

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2521-2536, 2023, DOI:10.32604/csse.2023.029336

Abstract Communication between people with disabilities and people who do not understand sign language is a growing social need and can be a tedious task. One of the main functions of sign language is to communicate with each other through hand gestures. Recognition of hand gestures has become an important challenge for the recognition of sign language. There are many existing models that can produce a good accuracy, but if the model test with rotated or translated images, they may face some difficulties to make good performance accuracy. To resolve these challenges of hand gesture recognition, we proposed a Rotation, Translation… More >

Vinay Gautam¹, Naresh Kumar Trivedi¹, Abhineet Anand¹, Rajeev Tiwari^2,*, Atef Zaguia³, Deepika Koundal⁴, Sachin Jain⁵

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2259-2275, 2023, DOI:10.32604/csse.2023.026358

Abstract Skin lesions detection and classification is a prominent issue and difficult even for extremely skilled dermatologists and pathologists. Skin disease is the most common disorder triggered by fungus, viruses, bacteria, allergies, etc. Skin diseases are most dangerous and may be the cause of serious damage. Therefore, it requires to diagnose it at an earlier stage, but the diagnosis therapy itself is complex and needs advanced laser and photonic therapy. This advance therapy involves financial burden and some other ill effects. Therefore, it must use artificial intelligence techniques to detect and diagnose it accurately at an earlier stage. Several techniques have… More >

Tamara al Shloul¹, Israr Akhter², Suliman A. Alsuhibany³, Yazeed Yasin Ghadi⁴, Ahmad Jalal², Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2389-2405, 2022, DOI:10.32604/cmc.2022.027007

Abstract E-learning approaches are one of the most important learning platforms for the learner through electronic equipment. Such study techniques are useful for other groups of learners such as the crowd, pedestrian, sports, transports, communication, emergency services, management systems and education sectors. E-learning is still a challenging domain for researchers and developers to find new trends and advanced tools and methods. Many of them are currently working on this domain to fulfill the requirements of industry and the environment. In this paper, we proposed a method for pedestrian behavior mining of aerial data, using deep flow feature, graph mining technique, and… More >