Effective detection of skin cancer utilizing images is a challenging issue in the healthcare domain. Skin disease detection is a time-consuming operation and if detected at later stages, may lead to death. This paper devises a novel hybrid Quantum …

Colonoscopy is an important method for the prevention and early detection of colorectal cancer, commonly used to detect polyps associated with colorectal cancer. However, accurate polyp segmentation still faces significant challenges: (1) polyps …

Traditional graph neural networks (GNNs) typically understand graph data from a single view, which tends to over-look the multiple semantic information contained in graphs. However, the properties of graphs are usually determined by some …

Contrastive learning is an effective method of self-supervised representation learning, which has made significant strides in the application of sentence representation learning in recent years. However, most previous studies typically focus on …

Internet services have led to the eruption of network traffic, and machine learning on these Internet data has become an indispensable tool, especially when the application is risk-sensitive. This paper focuses on network traffic classification in …

In recent years, large-kernel Convolutional Neural Networks (CNNs) have received significant attention in the classification of COVID-19 X-ray images. However, there are still unresolved issues. Existing large-kernel convolutional neural networks …

Failure of concrete slabs in shear is a devastating incident which could result in catastrophic disasters suddenly without warning. Though, the use of prestressing in concrete slabs reduces the warning even further, thus leading to an increased …

In visible-infrared video person re-identification (re-ID), the key to solving cross-modal pedestrian identity matching lies in extracting features that are robust to complex scene variations, including modality, camera viewpoints, pedestrian …

Abstractive text summarization aims to paraphrase the given corpus and generate new sentences while retaining key information. In recent works, abstractive summarization task has been commonly modeled using Transformers, which are fine-tuned by …

In hierarchical classification learning, data categories exhibit a hierarchical structure. Many studies only have focused on category structure information, knowledge and data correlation are often overlooked. Based on this, a Hierarchical Feature …

The agriculture sectors, which account for approximately 50% of the worldwide economic production, are the fundamental cornerstone of each nation. The significance of precision agriculture cannot be understated in assessing crop conditions and …

Parkinson’s disease is a fatal incurable neurological disorder that affects the nervous system of the brain and causes several health problems including rigidity, tremors, Bradykinesia, and so on. Timely and accurate Parkinson’s disease detection …

Aspect sentiment triplet extraction (ASTE) is a challenging sub-task within aspect-based sentiment analysis. Its goal is to extract aspects, opinions, and sentiment polarities from review sentences. Even though researchers have tried using …

Classroom management is a crucial component in ensuring teaching quality. However, traditional methods that rely primarily on manual processes cannot provide continuous assessments in an unobtrusive manner. Recently, previous studies that have …

The rapid expansion of wireless communication systems and on-demand computing resources over the internet has created new opportunities and challenges in ensuring the accessibility and security of critical infrastructure. Cyberattacks in various …

Accurately predicting link signs in signed graphs remains challenging due to the need to capture detailed node-level interactions and dynamic higher-order group relationships. We propose a novel dual-channel graph convolutional network that …

Deep neural networks (DNNs) have achieved impressive performance in various applications, but are susceptible to overfitting biases in training data, such as label noise and class imbalance. Example reweighting methods can be used to solve this …

In recent years, the emergence of neural architecture search (NAS) has brought a series of breakthroughs to the field of computer vision. However, existing NAS methods either overly focus on optimizing for classification accuracy, resulting in …

Medical images (MI) contain both diagnostic information and sensitive personal data and they are usually exchanged between doctors, patients, hospitals and public networks. Therefore, it is essential to ensure safety during storage and …

In recent years, the proliferation of malware production tools and the advancement of ChatGPT has led to a significant increase in the number of malware and its variants. Consequently, the detection of malware families has become increasingly …