Latest AI and machine learning research in adhd/add for healthcare professionals.
Self Supervised Representation Learning (SSRepL) can capture meaningful and robust representations of the Attention Deficit Hyperactivity Disorder (ADHD) data and have the potential to improve the model's performance on also downstream different types of Neurodevelopmental disorder (NDD) detection. In this paper, a novel SSRepL and Transfer Learning (TL)-based framework that incorporates a Long ...
We propose ``Shape from Semantics'', which is able to create 3D models whose geometry and appearance match given semantics when observed from different views. Traditional ``Shape from X'' tasks usually use visual input (e.g., RGB images or depth maps) to reconstruct geometry, imposing strict constraints that limit creative explorations. As applications, works like Shadow Art and Wire Art often s...
This study presents a narrative review of the use of digital health technologies (DHTs) and artificial intelligence to screen and mitigate risks and...
We present a Reinforcement Learning Platform for Adversarial Black-box untargeted and targeted attacks, RLAB, that allows users to select from vario...
Diffusion-based generative models have achieved remarkable progress in visual content generation. However, traditional diffusion models directly den...
Recent advancements in deep learning have significantly improved performance on computer vision tasks. Previous image classification methods primari...
Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a cruci...
This paper investigates predicting market strength solely from candlestick chart images to assist investment decisions. The core research problem is...
Dark-field radiography of the human chest has been demonstrated to have promising potential for the analysis of the lung microstructure and the diag...
Effective and reliable control over large language model (LLM) behavior is a significant challenge. While activation steering methods, which add ste...
Throughout history, humans have created remarkable works of art, but artificial intelligence has only recently started to make strides in generating...
Remote sensing visual question answering (RSVQA) is a task that automatically extracts information from satellite images and processes a question to...
Superpixel segmentation is a foundation for many higher-level computer vision tasks, such as image segmentation, object recognition, and scene under...
What types of numeric representations emerge in neural systems? What would a satisfying answer to this question look like? In this work, we interpre...
Online Learning Management Systems (LMSs), such as Blackboard and Canvas, have existed for decades. Yet, course readings, when provided at all, cons...
Advancements in robotics have opened possibilities to automate tasks in various fields such as manufacturing, emergency response and healthcare. How...
The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely accessibl...
Reducing computational costs is an important issue for development of embedded systems. Binary-weight Neural Networks (BNNs), in which weights are b...
The parsing of sensory information into discrete topographic domains is a fundamental principle of sensory processing. In the auditory cortex, these d...
From rodents to humans, animals constantly face a central question: is the reward worth the effort? Effort and reward sensitivity in such situations v...