Actinic keratosis (AK) is a common precancerous skin lesion with significant harm, and it is often confused with non-actinic keratoses (NAK). At present, the diagnosis of AK mainly depends on clinical experience and histopathology. Due to the high di...
Efficient and accurate vision models are essential for real-world applications such as medical imaging and deepfake detection, where both performance and computational efficiency are critical. While recent vision models achieve high accuracy, they of...
Pneumonia has been directly responsible for a huge number of deaths all across the globe. Pneumonia shares visual features with other respiratory diseases, such as tuberculosis, which can make it difficult to distinguish between them. Moreover, there...
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...
Water level monitoring is closely linked to the safety of production and daily activities along riverbanks, making real-time and high-precision water level measurement an urgent technical demand. The feature extraction backbone of the Unet model is m...
Distracted human driver detection is an important feature that should be included in most levels of autonomous cars, because most of these are still under development. Hereby, this paper proposes an architecture to perform this task in a fast and acc...
More than 60 percent of the global surface is covered by clouds, and they play a vital role in the hydrological circle, climate change, and radiation budgets by modifying shortwaves and longwave. Weather forecast reports are critical to areas such as...
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...
An accurate stand count is a prerequisite to determining the emergence rate, assessing seedling vigor, and facilitating site-specific management for optimal crop production. Traditional manual counting methods in stand assessment are labor intensive...
Accurate diagnosis of pediatric pneumonia remains a challenging task in clinical practice. The aim of this research is to propose a hybrid ensemble framework for pediatric pneumonia diagnosis that unites three fine-tuned pre-trained CNN models throug...
This paper proposes PestNet, a lightweight method for classifying crop pests, which improves upon MobileNet-V2 to address the high model complexity and low classification accuracy commonly found in pest classification research. Firstly, the training...
Existing facial expression recognition methods have some drawbacks. For example, it becomes difficult for network learning on cross-dataset facial expressions, multi-region learning on an image did not extract the overall image information, and a fre...
The classification of germinated pole sitao (Vigna unguiculata (L.) Walp.) seeds is important in seed germination tests. The automation of this process has been explored for different grain and legume seeds but is only limited to binary classificatio...
Accurate and timely monitoring of pests is an effective way to minimize the negative effects of pests in agriculture. Since deep learning-based methods have achieved good performance in object detection, they have been successfully applied for pest d...
Many individuals worldwide pass away as a result of inadequate procedures for prompt illness identification and subsequent treatment. A valuable life can be saved or at least extended with the early identification of serious illnesses, such as variou...
The issues of inadequate digital proficiency among agricultural practitioners and the suboptimal image quality captured using mobile smart devices have been addressed by providing appropriate guidance to photographers to properly position their mobil...
Facial emotion recognition has become increasingly important in healthcare, where understanding delicate cues like pain, discomfort, or unconsciousness can support more timely and responsive care. Yet, recognizing facial expressions in real-world set...
We present a new deep learning architecture, named SynthSecureNet, which hybridizes two popular architectures: MobileNetV2 and ResNetV2. The latter have been shown to be promising in violence detection. The aim of our architecture is to harness the c...
The precise, non-destructive monitoring of fish length and weight is a core technology for advancing intelligent aquaculture. However, this field faces dual challenges: traditional contact-based measurements induce stress and yield loss. In addition,...
Pilose antler is a valuable traditional Chinese medicinal herb. Slices of different grades show great disparities in medicinal potency and market price. Conventional visual discrimination of wax slices, powder slices, gauze slices and bone slices rel...
Due to their excellent strength-to-weight ratio, composite laminates are gradually being substituted for traditional metallic materials in a variety of industries. However, due to their orthotropic nature, composite laminates are prone to several dif...
Classifying remote sensing images is vital for interpreting image content. Presently, remote sensing image scene classification methods using convolutional neural networks have drawbacks, including excessive parameters and heavy calculation costs. Mo...
The recognition of fire at its early stages and stopping it from causing socioeconomic and environmental disasters remains a demanding task. Despite the availability of convincing networks, there is a need to develop a lightweight network for resourc...
Wildfires pose a major threat to ecosystems, property, and human life. Although transfer learning (TL) with deep neural networks has shown promise for satellite-image classification, performance can vary across model architectures. This study develop...
Early and accurate detection of pneumonia from chest X-ray images is essential for improving treatment and clinical outcomes. Medical imaging datasets often exhibit class imbalance and uncertainty in feature extraction, which complicates conventional...
Shiitake mushrooms are an important edible fungus, and their nutrient content is related to their quality. With the acceleration of urbanization, there has been a serious loss of population and shortage of labor in rural areas. The problem of harvest...
Lightweight vision models are widely deployed in mobile and embedded systems, where strict computational and memory budgets demand compact architectures. However, their evaluation remains dominated by ImageNet—a single, large natural-image data...
Aiming at the real-time object detection requirements of the intelligent control system for laboratory item transportation in mobile embedded unmanned vehicles, this paper proposes a lightweight hybrid detection system based on the OpenMV vision modu...
The maturity level of tomato is a key factor of tomato picking, which directly determines the transportation distance, storage time, and market freshness of postharvest tomato. In view of the lack of studies on tomato maturity classification under na...
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...
Face detection systems have generally been used primarily for non-masked faces, which include relevant facial characteristics such as the ears, chin, lips, nose, and eyes. Masks are necessary to cover faces in many situations, such as pandemics, crim...
Forest fires pose a significant threat to ecosystems, property, and human life, making their early and accurate detection crucial for effective intervention. This study presents a novel, lightweight approach to real-time forest fire detection that is...
Mobile Edge Computing (MEC) has emerged as a promising network computing paradigm associated with mobile devices at local areas to diminish network latency under the employment and utilization of cloud/edge computing resources. In that context, MEC s...
This paper proposes a residual network model integrated with an attention mechanism module for the detection and classification of malware on railway mobile terminals. To address the issues of insufficient and imbalanced samples, Wasserstein Generati...
In this paper, a Mobility Assistive System (NOVA-MAS) and a model-driven development approach are proposed to support the acquisition and analysis of data, infrastructures control, and dissemination of information along public roads. A literature rev...
To address the challenges of scarce anomaly samples, inadequate modeling of temporal dynamic features, and limited feature selection capability of lightweight models in industrial anomalous sound detection, this paper proposes a method under an unsup...
In this study, we conceptualize the demands imposed on emergency supply chains during extraordinary emergency events as “stress” and develop a scenario-based stress evolution (SE) analytical approach in emergency mobilization decision-mak...
Designing effective temporal modeling strategies for video-based sign language recognition (SLR) remains challenging, particularly in low-resource settings where the behavior of modern architectures is not fully understood. In this study, we present...
The rapid expansion of the Internet of Things (IoT) has uncovered a significant asymmetry in cybersecurity, where low-power edge devices must face sophisticated threats from adversaries backed by ample resources. In our study, we employ a symmetry-ba...
Globally, the transportation sector stands as the third largest contributor to greenhouse gas (GHG) emissions. Nepal is no exception, relying entirely on imported petroleum products. The capital city of Nepal, Kathmandu Valley, with its unique bowl-s...
The Face Anti-Spoofing (FAS) methods plays a very important role in ensuring the security of face recognition systems. The existing FAS methods perform well in short-distance scenarios, e.g., phone unlocking, face payment, etc. However, it is still c...
To solve problems such as the unstable detection performance of the sound anomaly detection of wind turbine gearboxes when only normal data are used for training, and the poor detection performance caused by the poor classification of samples with hi...
During the Keyhole Tungsten Inert Gas (K-TIG) welding process, a significant amount of information related to the weld quality can be obtained from the weld pool and the keyhole of the topside molten pool image, which provides a vital basis for the c...
Grapevine is a valuable and profitable crop that is susceptible to various diseases, making effective disease detection crucial for crop monitoring. This work explores the use of deep learning-based plant disease detection as an alternative to tradit...
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by difficulties in social communication and repetitive behaviors. The exact causes of ASD remain elusive and likely involve a combination of genetic, environmental,...
Due to the rapid emergence and evolution of AI applications, the utilization of smart imaging devices has increased significantly. Researchers have started using deep learning models, such as CNN, for image classification. Unlike the traditional mode...
In this paper, an improved MobileNetV3-Small algorithm model is proposed for the problem of poor real-time wildfire identification based on convolutional neural networks (CNNs). Firstly, a wildfire dataset is constructed and subsequently expanded thr...
Acute lymphoblastic leukemia (ALL) is one of the deadliest forms of leukemia due to the bone marrow producing many white blood cells (WBC). ALL is one of the most common types of cancer in children and adults. Doctors determine the treatment of leuke...
In exploring the flight delay problem, traditional deep learning algorithms suffer from low accuracy and extreme computational complexity; therefore, the deep flight delay prediction algorithm is difficult to directly deploy to the mobile terminal. I...
Proper plant leaf disease (PLD) detection is challenging in complex backgrounds and under different capture conditions. For this reason, initially, modified adaptive centroid-based segmentation (ACS) is used to trace the proper region of interest (RO...
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