Brain age serves as a vital biomarker for detecting neurological ailments like Alzheimer’s disease (AD) and Parkinson’s disease (PD). Magnetic resonance imaging (MRI) has been extensively explored with deep neural networks to estimate brain age.

Methods based on the physical Retinex model are effective in enhancing low-light images, adeptly handling the challenges posed by low signal-to-noise ratios and high noise in images captured under weak lighting conditions. However, traditional …

From an unstructured text, relation extraction (RE) predicts semantic relationships between pairs of entities. The process of labeling tokens and phrases can be very expensive and require a great deal of time and effort. The low-resource relation …

Malicious apps use a variety of methods to spread infections, take over computers and/or IoT devices, and steal sensitive data. Several detection techniques have been proposed to counter these attacks. Despite the promising results of recent …

Autism spectrum disorders (ASDs) pose complex challenges, characterized by atypical behaviors, sensory sensitivities, and difficulties in social interaction. Despite extensive research, their exact causes remain elusive, indicating a …

Does the model demonstrate exceptional proficiency in “item counting,” “color recognition,” or other Fundamental Visual Comprehension Capability (FVCC)? There have been remarkable advancements in the field of multimodal, the pretrained general …

Generative Artificial Intelligence models are Artificial Intelligence models that generate new content based on a prompt or input. The output content can be in various forms, including text, images, and video. Metaverse refers to a virtual world …

In the text mining area, prevalent deep learning models primarily focus on mapping input features to result of predicted outputs, which exhibit a deficiency in self-dialectical thinking process. Inspired by self-reflective mechanisms in human …

Although deep neural networks have developed at a high level, the large computational requirement limits the deployment in end devices. To this end, a variety of model compression and acceleration techniques have been developed. Among these …

Commonsense knowledge acquisition and representation is a core topic in artificial intelligence (AI), which is crucial for building more sophisticated and human-like AI systems. However, existing commonsense knowledge bases organize facts in an …

Multimodal models are designed to process different types of data within a single generative framework. The prevalent strategy in previous methods involves learning joint representations that are shared across different modalities. These joint …

Artificial intelligence (AI) systems are increasingly used in healthcare applications, although some challenges have not been completely overcome to make them fully trustworthy and compliant with modern regulations and societal needs. First of …

Aggregating the diverse features into a compact representation is a hot issue in image retrieval. However, aggregating the differential feature of multilayer into a discriminative representation remains challenging. Inspired by the value-guided …

Knowledge tracing (KT) is a technique that can be applied to predict students’ current skill mastery levels and future academic performance based on previous question-answering data. A good KT model can more accurately reflect a student’s …

In this paper, we target the problem of generating facial expressions from a piece of audio. This is challenging since both audio and video have inherent characteristics that are distinct from the other. Some words may have identical lip …

Sentence-level relation extraction is a technique for extracting factual information about relationships between entities from a sentence. However, the customary method overlooks the semantic information conveyed by the label itself, thereby …

Intelligent voice assistants, such as Apple Siri and Amazon Alexa, are widely used nowadays. These task-oriented dialogue systems require a semantic parsing module in order to process user utterances and understand the action to be performed. This …

“Micromobility” is a term that indicates tiny, lightweight vehicles with speeds lower than 30 km/h and driven personally by road users [ 37 ]. It has the potential to contribute toward the accomplishment of the sustainable development goals. Due to …

Early diagnosis plays a crucial role in controlling Alzheimer’s disease (AD) progression and delaying cognitive decline. Traditional diagnostic tools present great challenges to clinical practice due to their invasiveness, high cost, and …

Human language is influenced by sensory-motor experiences. Sensory experiences gathered in a spatiotemporal world are used as raw material to create more abstract concepts. In language, one way to encode spatial relationships is through spatial …