Face recognition in general scenarios has been saturated in recent years, but there is still room to enhance model performance in extreme scenarios and fairness situations. Inspired by the successful application of Transformer and ConvNet in computer...
Background: Breast cancer diagnosis increasingly relies on ultrasound imaging, but challenges related to operator dependency and image quality limitations necessitate automated segmentation approaches. Traditional U-Net architectures, while widely us...
The intelligent transportation system, especially autonomous vehicles, has seen a lot of interest among researchers owing to the tremendous work in modern artificial intelligence (AI) techniques, especially deep neural learning. As a result of increa...
The significance of environmental considerations has been highlighted by the substantial impact of plant pests on ecosystems. Addressing the urgent demand for sophisticated pest management solutions in arboreal environments, this study leverages adva...
Today, specific convolution neural network (CNN) models assigned to specific tasks are often used. In this article, the authors explored three models: MobileNet, EfficientNetB0, and InceptionV3 combined. The authors were interested in investigating h...
Real-time non-intrusive monitoring of wind turbines, blades, and defect surfaces poses a set of complex challenges related to accuracy, safety, cost, and computational efficiency. This work introduces an enhanced deep learning-based framework for rea...
Accurate and intelligent identification of rare and endangered individuals of flagship wildlife species, such as Amur tiger (Panthera tigris altaica), is crucial for understanding population structure and distribution, thereby facilitating targeted c...
Aflatoxin B1, a toxic carcinogen frequently contaminating almonds, nuts, and food products, poses significant health risks. Therefore, a rapid and non-destructive detection method is crucial to detect aflatoxin B1-contaminated almonds to ensure food...
This study addresses the growing need for effective energy management solutions in university settings, with particular emphasis on solar–hydrogen systems. The study’s purpose is to explore the integration of deep learning models, specifi...
Almonds are a highly valued nut due to their rich protein and nutritional content. However, they are vulnerable to aflatoxin B1 (AFB1) contamination in warm and humid environments. Consumption of AFB1-contaminated almonds can pose serious health risk...
Early diagnosis and preventive measures are necessary to mitigate diseases’ impact on the yield of Colocasia esculenta (Taro). This study addresses the challenges of Taro disease identification by employing two key strategies: integrating expla...
In the medical field, hematoxylin and eosin (H&E)-stained histopathology images of cell nuclei analysis represent an important measure for cancer diagnosis. The most valuable aspect of the nuclei analysis is the segmentation of the different nucl...
Building segmentation is crucial for applications extending from map production to urban planning. Nowadays, it is still a challenge due to CNNs’ inability to model global context and Transformers’ high memory need. In this study, 10 CNN...
Otitis media with effusion (OME), primarily seen in children aged 2 years and younger, is characterized by the presence of fluid in the middle ear, often resulting in hearing loss and aural fullness. While deep learning networks have been explored to...
In recent years, Single-Image Super-Resolution (SISR) has gained significant attention in the geoscience and remote sensing community for its potential to improve the resolution of low-quality underwater imagery. This paper introduces MIMAR-Net (Mult...
Sign languages are complex, but there are ongoing research efforts in engineering and data science to recognize, understand, and utilize them in real-time applications. Arabic sign language recognition (ArSL) has been examined and applied using vario...
Differential diagnosis between avascular necrosis (AVN) and transient osteoporosis of the hip (TOH) can be complicated even for experienced MSK radiologists. Our study attempted to use MR images in order to develop a deep learning methodology with th...
Deaf and hearing-impaired people always face communication barriers. Non-invasive surface electromyography (sEMG) sensor-based sign language recognition (SLR) technology can help them to better integrate into social life. Since the traditional tandem...
Plant diseases affect the availability and safety of plants for human and animal consumption and threaten food safety, thus reducing food availability and access, as well as reducing crop yield and quality. There is a need for novel disease detection...
This study explores advanced methods for plant disease classification by integrating pre-trained deep learning models and leveraging ensemble learning. After a comprehensive review of deep learning methods in this area, the InceptionResNetV2, MobileN...
The segmentation algorithm of cerebrovascular magnetic resonance angiography (MRA) images based on deep learning plays an essential role in medical study. Traditional segmentation algorithms face poor segmentation results and poor connectivity when t...
Brain cancer is a life-threatening disease requiring close attention. Early and accurate diagnosis using non-invasive medical imaging is critical for successful treatment and patient survival. However, manual diagnosis by radiologist experts is time-...
Energy system optimization seeks to utilize multiple energy sources efficiently under technical, economic, and environmental constraints. The increasing integration of renewable energy and the need for sustainable operation have made the optimal plan...
The IoT’s quick development has brought up several security problems and issues that cannot be solved using traditional intelligent systems. Deep learning (DL) in the field of artificial intelligence (AI) has proven to be efficient, with many a...
Hand gesture recognition (HGR) is a challenging and fascinating research topic in computer vision with numerous daily life applications. In HGR, computers aim to identify and classify hand gestures. The limited diversity of the dataset used in HGR is...
Brain tumour detection and classification are life-saving steps for humanity. There are many medical imaging techniques that can identify abnormal brain diseases. These include nuclear magnetic resonance, ultrasound, X-rays, radionuclides, lasers, el...
Retention of rice freshness is highly dependent on storage temperature. Timely and accurate identification of rice freshness is critical to ensure food security. Here, we characterize the freshness of rice in reference to storage temperature. Teraher...
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...
The intelligent use of deep learning (DL) techniques can assist in overcoming noise and uncertainty during fingerprinting-based localization. With the rise in the available computational power on mobile devices, it is now possible to employ DL techni...
Car crashes are among the top ten leading causes of death; they could mainly be attributed to distracted drivers. An advanced driver-assistance technique (ADAT) is a procedure that can notify the driver about a dangerous scenario, reduce traffic cras...
The modulation recognition of digital signals under non-cooperative conditions is one of the important research contents here. With the rapid development of artificial intelligence technology, deep learning theory is also increasingly being applied t...
Acute Lymphocytic Leukemia is a type of cancer that occurs when abnormal white blood cells are produced in the bone marrow which do not function properly, crowding out healthy cells and weakening the immunity of the body and thus its ability to resis...
22 January 2023
Since December 2019, the coronavirus disease has significantly affected millions of people. Given the effect this disease has on the pulmonary systems of humans, there is a need for chest radiographic imaging (CXR) for monitoring the disease and prev...
6 December 2023
This study focuses on leveraging data-driven techniques to diagnose brain tumors through magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we introduce and fine-tune two robust frameworks, ResNet 50 and Inception V3,...
Breast cancer has evolved as the most lethal illness impacting women all over the globe. Breast cancer may be detected early, which reduces mortality and increases the chances of a full recovery. Researchers all around the world are working on breast...
Human action recognition is a constantly evolving field that is driven by numerous applications. In recent years, significant progress has been made in this area due to the development of advanced representation learning techniques. Despite this prog...
Fibroids of the uterus are a common benign tumor affecting women of childbearing age. Uterine fibroids (UF) can be effectively treated with earlier identification and diagnosis. Its automated diagnosis from medical images is an area where deep learni...
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...
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...
27 September 2021
Coronavirus disease (COVID-19) spreads from one person to another rapidly. A recently discovered coronavirus causes it. COVID-19 has proven to be challenging to detect and cure at an early stage all over the world. Patients showing symptoms of COVID-...
Low Probability of Intercept (LPI) radar waveform recognition is not only an important branch of the electronic reconnaissance field, but also an important means to obtain non-cooperative radar information. To solve the problems of LPI radar waveform...
Alzheimer’s Disease, a progressive brain disorder that impairs memory, thinking, and behavior, has started to benefit from advancements in deep learning. However, the application of deep learning in medicine faces the challenge of limited data...
Noise reduction is a critical step in seismic data processing. A novel strong noise reduction network is proposed in this study. The network enhances the U-Net architecture with an improved inception module and coordinate attention (CA) mechanism, su...
Generative adversarial networks (GANs) are increasingly used for image enhancement tasks like denoising, super-resolution, and artifact removal. In this study, we propose a robust GAN-based architecture featuring a U-Net-style generator and DCNN-base...
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...
3 December 2024
Ensuring the quality of medicinal herbs in the herbal market is crucial. However, the genetic and physical similarities among medicinal materials have led to issues of mixing and counterfeit distribution, posing significant challenges to quality assu...
Rapid reconstruction of finite-element stress distributions can support preliminary screening when many related two-dimensional geometries must be examined in a fixed mechanical setting. This study presents a revised RSP-Net for reconstructing normal...
Plants diseases constitute a substantial threat for farmers given the high economic and environmental impact of their treatment. Detecting possible pathogen threats in plants based on non-destructive remote sensing and computer vision methods offers...
Wake vortices generated by aircraft during near-ground operations have a significant impact on airport safety during takeoffs and landings. Identifying wake vortices in complex airspaces assists air traffic controllers in making informed decisions, e...
Waste disposal remains a challenge due to land availability, and environmental and health issues related to the main disposal method, landfilling. Combining computer vision (machine learning) and robotics to sort waste is a cost-effective solution fo...
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