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Identifying and Reporting Dependent Adult abuse

Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.

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Optimizing functional brain network analysis by incorporating nonlinear factors and frequency band selection with machine learning models.

The accurate assessment of the brain's functional network is seen as crucial for the understanding o...

Feb 2025 40020107
The NeRF Signature: Codebook-Aided Watermarking for Neural Radiance Fields

Neural Radiance Fields (NeRF) have been gaining attention as a significant form of 3D content repr...

Symmetrical Visual Contrastive Optimization: Aligning Vision-Language Models with Minimal Contrastive Images

Recent studies have shown that Large Vision-Language Models (VLMs) tend to neglect image content a...

MGFI-Net: A Multi-Grained Feature Integration Network for Enhanced Medical Image Segmentation

Medical image segmentation plays a crucial role in various clinical applications. A major challeng...

From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms

When an individual reports a negative interaction with some system, how can their personal experie...

Amnesia as a Catalyst for Enhancing Black Box Pixel Attacks in Image Classification and Object Detection

It is well known that query-based attacks tend to have relatively higher success rates in adversar...

DCENWCNet: A Deep CNN Ensemble Network for White Blood Cell Classification with LIME-Based Explainability

White blood cells (WBC) are important parts of our immune system, and they protect our body agains...

MapFusion: A Novel BEV Feature Fusion Network for Multi-modal Map Construction

Map construction task plays a vital role in providing precise and comprehensive static environment...

HSI: A Holistic Style Injector for Arbitrary Style Transfer

Attention-based arbitrary style transfer methods have gained significant attention recently due to...

The Skin Game: Revolutionizing Standards for AI Dermatology Model Comparison

Deep Learning approaches in dermatological image classification have shown promising results, yet ...

MORPH-LER: Log-Euclidean Regularization for Population-Aware Image Registration

Spatial transformations that capture population-level morphological statistics are critical for me...

Enhancing Environmental Robustness in Few-shot Learning via Conditional Representation Learning

Few-shot learning (FSL) has recently been extensively utilized to overcome the scarcity of trainin...

Ovarian-adnexal reporting and data system MRI scoring: diagnostic accuracy, interobserver agreement, and applicability to machine learning.

OBJECTIVES: To evaluate the interobserver agreement and diagnostic accuracy of ovarian-adnexal repor...

Feb 2025 39471474
UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent

Recent advancements in Vision-Language-Action (VLA) models have leveraged pre-trained Vision-Langu...

A Tale of Three Location Trackers: AirTag, SmartTag, and Tile

Bluetooth Low Energy (BLE) location trackers, or "tags", are popular consumer devices for monitori...

Detecting Unauthorized Drones with Cell-Free Integrated Sensing and Communication

Integrated sensing and communication (ISAC) boosts network efficiency by using existing resources ...

Improved Vessel Segmentation with Symmetric Rotation-Equivariant U-Net

Automated segmentation plays a pivotal role in medical image analysis and computer-assisted interv...

Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling

Artificial intelligence (AI) systems in healthcare have demonstrated remarkable potential to impro...

FDG-Diff: Frequency-Domain-Guided Diffusion Framework for Compressed Hazy Image Restoration

In this study, we reveal that the interaction between haze degradation and JPEG compression introd...

Spatially-Delineated Domain-Adapted AI Classification: An Application for Oncology Data

Given multi-type point maps from different place-types (e.g., tumor regions), our objective is to ...

MASS: Overcoming Language Bias in Image-Text Matching

Pretrained visual-language models have made significant advancements in multimodal tasks, includin...

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