Latest AI and machine learning research in adhd/add for healthcare professionals.
Presentation Attack Detection (PAD) systems are usually designed independently of the fingerprint verification system. While this can be acceptable for use cases where specific user templates are not predetermined, it represents a missed opportunity to enhance security in scenarios where integrating PAD with the fingerprint verification system could significantly leverage users' templates, which...
Neuro-developmental disorders are manifested as dysfunctions in cognition, communication, behaviour and adaptability, and deep learning-based computer-aided diagnosis (CAD) can alleviate the increasingly strained healthcare resources on neuroimaging. However, neuroimaging such as fMRI contains complex spatio-temporal features, which makes the corresponding representations susceptible to a variet...
For effective image segmentation, it is crucial to employ constraints informed by prior knowledge about the characteristics of the areas to be segme...
In modern society, Attention-Deficit/Hyperactivity Disorder (ADHD) is one of the common mental diseases discovered not only in children but also in ...
In open data sets of functional magnetic resonance imaging (fMRI), the heterogeneity of the data is typically attributed to a combination of factors...
The predictions of click through rate (CTR) and conversion rate (CVR) play a crucial role in the success of ad-recommendation systems. A Deep Hierar...
Although multimodal large language models (MLLMs) exhibit remarkable reasoning capabilities on complex multimodal understanding tasks, they still su...
Multimodal remote sensing image registration aligns images from different sensors for data fusion and analysis. However, current methods often fail ...
Creativity in AI imagery remains a fundamental challenge, requiring not only the generation of visually compelling content but also the capacity to ...
Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children, characterized by difficulties in attention, hyp...
Chronic Kidney Disease (CKD) is a major global health issue which is affecting million people around the world and with increasing rate of mortality...
Diffusion models are widely used for image editing tasks. Existing editing methods often design a representation manipulation procedure by curating ...
The increasing demand for augmented and virtual reality applications has highlighted the importance of crafting immersive 3D scenes from a simple si...
Understanding how the brain's complex nonlinear dynamics give rise to adaptive cognition and behavior is a central challenge in neuroscience. These ...
Fitness can help to strengthen muscles, increase resistance to diseases, and improve body shape. Nowadays, a great number of people choose to exerci...
The current state-of-the-art methods in domain adaptive object detection (DAOD) use Mean Teacher self-labelling, where a teacher model, directly der...
Deep generative models have been used in style transfer tasks for images. In this study, we adapt and improve CycleGAN model to perform music style ...
Integrating functional magnetic resonance imaging (fMRI) connectivity data with phenotypic textual descriptors (e.g., disease label, demographic dat...
3D Gaussian Splatting (3D-GS) has revolutionized novel view synthesis with its efficient, explicit representation. However, it lacks frequency inter...
IP anycast is a widely adopted technique in which an address is replicated at multiple locations, to, e.g., reduce latency and enhance resilience. D...