Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
Protocol Reverse Engineering (PRE) is used to analyze protocols by inferring their structure and behavior. However, current PRE methods mainly focus on field identification within a single protocol and neglect Protocol State Machine (PSM) analysis in mixed protocol environments. This results in insufficient analysis of protocols' abnormal behavior and potential vulnerabilities, which are crucial...
Recent text-to-image diffusion models leverage cross-attention layers, which have been effectively utilized to enhance a range of visual generative tasks. However, our understanding of cross-attention layers remains somewhat limited. In this study, we introduce a mechanistic interpretability approach for diffusion models by constructing Head Relevance Vectors (HRVs) that align with human-specifi...
Recovering a physics-driven model, i.e. a governing set of equations of the underlying dynamical systems, from the real-world data has been of recen...
With the emergence of large-scale vision-language models, realistic radiology reports may be generated using only medical images as input guided by ...
We introduce a new framework, dubbed Cerberus, for attribute-based person re-identification (reID). Our approach leverages person attribute labels t...
This study aims to place Lorenzo Magnanis Eco-Cognitive Computationalism within the broader context of current work on information, computation, and...
Event cameras operate fundamentally differently from traditional Active Pixel Sensor (APS) cameras, offering significant advantages. Recent research...
Radiology reporting generative AI holds significant potential to alleviate clinical workloads and streamline medical care. However, achieving high c...
Age of Incorrect Information (AoII) is particularly relevant in systems where real time responses to anomalies are required, such as natural disaste...
Optical data center networks (DCNs) are renovating the infrastructure design for the cloud in the post Moore's law era. The fact that optical DCNs r...
We live in a world that is experiencing an unprecedented boom of AI applications that increasingly penetrate and enhance all sectors of private and ...
In the medical field, the limited availability of large-scale datasets and labor-intensive annotation processes hinder the performance of deep model...
Non-consensual intimate media (NCIM) inflicts significant harm. Currently, victim-survivors can use two mechanisms to report NCIM - as a non-consens...
Understanding neurological disorder is a fundamental problem in neuroscience, which often requires the analysis of brain networks derived from funct...
Automatic Medical Imaging Narrative generation aims to alleviate the workload of radiologists by producing accurate clinical descriptions directly f...
Machine learning (ML) and prediction modelling have become increasingly influential in healthcare, providing critical insights and supporting clinical...
Emergency departments (EDs) are pivotal in detecting child abuse and neglect, but this task is often complex. Our study developed a machine learning m...
Accurate prediction of temporal QoS is crucial for maintaining service reliability and enhancing user satisfaction in dynamic service-oriented envir...
Background Radiology practices have a high volume of unremarkable chest radiographs and artificial intelligence (AI) could possibly improve workflow b...
Predicting the strength of promoters and guiding their directed evolution is a crucial task in synthetic biology. This approach significantly reduces ...