Latest AI and machine learning research in adhd/add for healthcare professionals.
In image processing, solving inverse problems is the task of finding plausible reconstructions of an image that was corrupted by some (usually known) degradation model. Commonly, this process is done using a generative image model that can guide the reconstruction towards solutions that appear natural. The success of diffusion models over the last few years has made them a leading candidate for ...
With billions of smartphones in use globally, the daily time spent on these devices contributes significantly to overall electricity consumption. Given this scale, even minor reductions in smartphone power use could result in substantial energy savings. This study explores the impact of Lambda functions on resource consumption in mobile programming. While Lambda functions are known for enhancing...
Federated learning (FL) has enabled the training of multilingual large language models (LLMs) on diverse and decentralized multilingual data, especi...
We present an approach to model-based RL that achieves a new state of the art performance on the challenging Craftax-classic benchmark, an open-worl...
Self Supervised Representation Learning (SSRepL) can capture meaningful and robust representations of the Attention Deficit Hyperactivity Disorder (...
We propose ``Shape from Semantics'', which is able to create 3D models whose geometry and appearance match given semantics when observed from differ...
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...