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Identifying and Reporting Child abuse

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

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Showing 22-42 of 2,668 articles
An LLM-based hybrid approach for enhanced automated essay scoring.

Automated Essay Scoring systems have traditionally relied on shallow lexical data, such as word freq...

DGPrompt: Dual-guidance prompts generation for vision-language models.

Introducing learnable prompts into CLIP and fine-tuning them have demonstrated excellent performance...

Influence Enhanced Sparse Coordination Graphs for Multi-Agent Reinforcement Learning.

In contemporary Multi-Agent Reinforcement Learning (MARL), effectively enhancing the expressive capa...

DNA Molecular Computing with Weighted Signal Amplification for Cancer miRNA Biomarker Diagnostics.

The expression levels of microRNAs (miRNAs) are strongly linked to cancer progression, making them p...

Exploration and exploitation in continual learning.

Continual learning (CL) has received a surge of interest, particularly in parameter isolation approa...

Drug-Target Affinity Prediction Based on Topological Enhanced Graph Neural Networks.

Graph neural networks (GNNs) have achieved remarkable success in drug-target affinity (DTA) analysis...

CCA: Contrastive cluster assignment for supervised and semi-supervised medical image segmentation.

Transformers have shown great potential in vision tasks such as semantic segmentation. However, most...

A malware classification method based on directed API call relationships.

In response to the growing complexity of network threats, researchers are increasingly turning to ma...

scMDCL: A Deep Collaborative Contrastive Learning Framework for Matched Single-Cell Multiomics Data Clustering.

Single-cell multiomics clustering integrates multiple omics data to analyze cellular heterogeneity a...

Decoding Drug Response With Structurized Gridding Map-Based Cell Representation.

A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repu...

Efficient Brain Tumor Detection and Segmentation Using DN-MRCNN With Enhanced Imaging Technique.

This article proposes a method called DenseNet 121-Mask R-CNN (DN-MRCNN) for the detection and segme...

EMBANet: A flexible efficient multi-branch attention network.

Recent advances in the design of convolutional neural networks have shown that performance can be en...

Spatial heterogeneity effect of built environment on traffic safety using geographically weighted atrous convolutions neural network.

The built environment exerts a significant influence on the frequency and severity of traffic accide...

FLANet: A multiscale temporal convolution and spatial-spectral attention network for EEG artifact removal with adversarial training.

Denoising artifacts, such as noise from muscle or cardiac activity, is a crucial and ubiquitous conc...

Deep learning powered single-cell clustering framework with enhanced accuracy and stability.

Single-cell RNA sequencing (scRNA-seq) has revolutionized the field of cellular diversity research. ...

Pan-sharpening via Symmetric Multi-Scale Correction-Enhancement Transformers.

Pan-sharpening is a widely employed technique for enhancing the quality and accuracy of remote sensi...

Segmentation of coronary artery and calcification using prior knowledge based deep learning framework.

BACKGROUND: Computed tomography angiography (CTA) is used to screen for coronary artery calcificatio...

UNAGI: Unified neighbor-aware graph neural network for multi-view clustering.

Multi-view graph refining-based clustering (MGRC) methods aim to facilitate the clustering of data v...

Contrastive independent subspace analysis network for multi-view spatial information extraction.

Multi-view classification integrates features from different views to optimize classification perfor...

A universal strategy for smoothing deceleration in deep graph neural networks.

Graph neural networks (GNNs) have shown great promise in modeling graph-structured data, but the ove...

Unsupervised Domain Adaptation for EM Image Denoising With Invertible Networks.

Electron microscopy (EM) image denoising is critical for visualization and subsequent analysis. Desp...

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