The traditional cover modification steganography method only has low steganography ability. We propose a steganography method based on the convolutional neural network architecture (Xception) of deep separable convolutional layers in order to solve t...
Speech emotion recognition (SER) is an emerging technology that utilizes speech sounds to identify a speaker’s emotional state. Computational intelligence is receiving increasing attention from academics, health, and social media applications....
The fast and accurate identification of apple leaf diseases is beneficial for disease control and management of apple orchards. An improved network for apple leaf disease classification and a lightweight model for mobile terminal usage was designed i...
With the dramatic increase of the global population and with food insecurity increasing, it has become a major concern for both individuals and governments to fulfill the need for foods such as vegetables and fruits. Moreover, the desire for the cons...
In order to confront the challenge of efficiently evaluating interior wind noise levels in passenger vehicles during the early stages of shape design, this paper proposes a methodology for predicting interior wind noise. The methodology integrates ve...
Early detection and timely breast cancer treatment improve survival rates and patients’ quality of life. Hence, many computer-assisted techniques based on artificial intelligence are being introduced into the traditional diagnostic workflow. Th...
Rapid and precise identification of Coronavirus Disease 2019 (COVID-19) is pivotal for effective patient care, comprehending the pandemic’s trajectory, and enhancing long-term patient survival rates. Despite numerous recent endeavors in medical...
Computed tomography (CT) scans, or radiographic images, were used to aid in the early diagnosis of patients and detect normal and abnormal lung function in the human chest. However, the diagnosis of lungs infected with coronavirus disease 2019 (COVID...
Olive fruits at different ripening stages give rise to various table olive products and oil qualities. Therefore, developing an efficient method for recognizing and sorting olive fruits based on their ripening stages can greatly facilitate post-harve...
One of the leading forms of cancer is colorectal cancer (CRC), which is responsible for increasing mortality in young people. The aim of this paper is to provide an experimental modification of deep learning of Xception with Swish and assess the poss...
The automated and accurate results of classifying histopathology images are necessary in the early detection of cancer, especially the common cancers such as Colorectal Cancer (CRC) and Lung Cancer (LC). Nonetheless, classical deep learning framework...
Traditionally, condition monitoring of wind turbines has been performed manually by certified rope teams. This method of inspection can be dangerous for the personnel involved, and the resulting downtime can be expensive. Wind turbine inspection can...
The novel coronavirus 2019 (COVID-19) spread rapidly around the world and its outbreak has become a pandemic. Due to an increase in afflicted cases, the quantity of COVID-19 tests kits available in hospitals has decreased. Therefore, an autonomous de...
Skin cancer is a major public health concern around the world. Skin cancer identification is critical for effective treatment and improved results. Deep learning models have shown considerable promise in assisting dermatologists in skin cancer diagno...
Facial expression recognition (FER) utilizes artificial intelligence for the detection and analysis of human faces, with significant applications across various scenarios. Our objective is to deploy the facial emotion recognition network on mobile de...
The advent of artificial intelligence (AI) in animal husbandry, particularly in pig interaction recognition (PIR), offers a transformative approach to enhancing animal welfare, promoting sustainability, and bolstering climate resilience. This innovat...
Electric motors play a crucial role in self-driving vehicles. Therefore, fault diagnosis in motors is important for ensuring the safety and reliability of vehicles. In order to improve fault detection performance, this paper proposes a motor fault di...
One of the most promising research initiatives in the healthcare field is focused on the rising incidence of skin cancer worldwide and improving early discovery methods for the disease. The most significant factor in the fatalities caused by skin can...
This paper proposes a lightweight facial expression recognition model based on an improved Mini-Xception algorithm to address the issue of deploying existing models on resource-constrained devices. The model achieves lightweight facial expression rec...
In medical diagnostics, brain tumor classification remains essential, as accurate and efficient models aid medical professionals in early detection and treatment planning. Deep learning methodologies for brain tumor classification have gained popular...
Background/Objectives: Early and accurate diagnosis of skin cancer improves survival rates; however, dermatologists often struggle with lesion detection due to similar pigmentation. Deep learning and transfer learning models have shown promise in dia...
Malignant lymphoma, which impacts the lymphatic system, presents diverse challenges in accurate diagnosis due to its varied subtypes—chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and mantle cell lymphoma (MCL). Lymphoma is a for...
This study discusses the optimization of municipal solid waste management through the implementation of automated waste sorting systems, comparing two advanced artificial intelligence methodologies: Vertex AI and convolutional neural network (CNN) ar...
Wind turbine blade maintenance is expensive, dangerous, time-consuming, and prone to misdiagnosis. A potential solution to aid preventative maintenance is using deep learning and drones for inspection and early fault detection. In this research, five...
As climate change and human activity increase the likelihood of devastating wildfires, the need for early fire detection methods is inevitable. Although, it has been shown that deep learning and artificial intelligence can offer a solution to this pr...
The modern scientific world continuously endeavors to battle and devise solutions for newly arising pandemics. One such pandemic which has turned the world’s accustomed routine upside down is COVID-19: it has devastated the world economy and de...
Brain tumor diagnosis is a complex task due to the intricate anatomy of the brain and the heterogeneity of tumors. While magnetic resonance imaging (MRI) is commonly used for brain imaging, accurately detecting brain tumors remains challenging. This...
Automatic detection of tire defects has become an important issue for tire production companies since these defects cause road accidents and loss of human lives. Defects in the inner structure of the tire cannot be detected with the naked eye; thus,...
Autism spectrum disorder (ASD) is a complicated neurological developmental disorder that manifests itself in a variety of ways. The child diagnosed with ASD and their parents’ daily lives can be dramatically improved with early diagnosis and ap...
Facial emotion recognition (FER) systems are imperative in recent advanced artificial intelligence (AI) applications to realize better human–computer interactions. Most deep learning-based FER systems have issues with low accuracy and high reso...
Background and Motivation: COVID-19 has resulted in a massive loss of life during the last two years. The current imaging-based diagnostic methods for COVID-19 detection in multiclass pneumonia-type chest X-rays are not so successful in clinical prac...
22 July 2024
Background: Intracranial neoplasm, often referred to as a brain tumor, is an abnormal growth or mass of tissues in the brain. The complexity of the brain and the associated diagnostic delays cause significant stress for patients. This study aims to e...
Wind turbine inspections are traditionally performed by certified rope teams, a manual process that poses safety risks to personnel and leads to operational downtime, resulting in revenue loss. To address some of these challenges, this study explores...
The COVID-19 pandemic has claimed the lives of millions of people and put a significant strain on healthcare facilities. To combat this disease, it is necessary to monitor affected patients in a timely and cost-effective manner. In this work, CXR ima...
The application of artificial intelligence (AI) such as deep learning in the quality control of grains has the potential to assist analysts in decision making and improving procedures. Advanced technologies based on X-ray imaging provide markedly eas...
The rise of deepfakes—synthetic media generated using artificial intelligence—threatens digital content authenticity, facilitating misinformation and manipulation. However, deepfakes can also depict real or entirely fictitious individuals...
A vital problem faced by urban areas, traffic congestion impacts wealth, climate, and air pollution in cities. Sustainable transportation systems (STSs) play a crucial role in traffic congestion prediction for adopting transportation networks to impr...
This study examines the utilization of deep learning and transfer learning models for classifying photos of Indian cuisine. Indian cuisine, characterized by its extensive diversity and intricate presentation, poses considerable hurdles in food recogn...
Coronavirus (COVID-19) is a fast-spreading virus-related disease. On 28 March 2022, Worldometer (COVID-19 live update) reported that there were about 482,338,923 COVID-19 cases and 6,149,387 fatalities worldwide. Moreover, there were about 416,884,71...
Lung cancer is among the most hazardous types of cancer in humans. The correct diagnosis of pathogenic lung disease is critical for medication. Traditionally, determining the pathological form of lung cancer involves an expensive and time-consuming p...
Pectus excavatum (PE), a chest-wall deformity that can compromise cardiopulmonary function, cannot be detected by a radiologist through frontal chest radiography without a lateral view or chest computed tomography. This study aims to train a convolut...
The impact analysis of deep learning models for COVID-19-infected X-ray images is an extremely challenging task. Every model has unique capabilities that can provide suitable solutions for some given problem. The prescribed work analyzes various deep...
Image segmentation is an essential step in image analysis that brings meaning to the pixels in the image. Nevertheless, it is also a difficult task due to the lack of a general suited approach to this problem and the use of real-life pictures that ca...
Deepfake technology poses significant threats in various domains, including politics, cybersecurity, and social media. This study uses the golden frame selection technique to present a neural network ensemble method for deepfake classification. The p...
Breast cancer is a significant health concern among women. Prompt diagnosis can diminish the mortality rate and direct patients to take steps for cancer treatment. Recently, deep learning has been employed to diagnose breast cancer in the context of...
Facial emotion recognition (FER) systems play a significant role in identifying driver emotions. Accurate facial emotion recognition of drivers in autonomous vehicles reduces road rage. However, training even the advanced FER model without proper dat...
One of the critical problems in multiclass classification tasks is the imbalance of the dataset. This is especially true when using contemporary pre-trained neural networks, where the last layers of the neural network are retrained. Therefore, large...
Silent speech decoding is a novel application of the Brain–Computer Interface (BCI) based on articulatory neuromuscular activities, reducing difficulties in data acquirement and processing. In this paper, spatial features and decoders that can...
Potato crop has become integral part of our diet due to its wide use in variety of dishes, making it an important food crop. Its importance also stems from the fact that it is one of the cheapest vegetables available throughout the year. This makes i...
Emotion recognition commonly relies on single-modal recognition methods, such as voice and video signals, which demonstrate a good practicability and universality in some scenarios. Nevertheless, as emotion-recognition application scenarios continue...
of 9