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Latest AI and machine learning research in smoking & tobacco for healthcare professionals.

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A multi-scale lithium-ion battery capacity prediction using mixture of experts and patch-based MLP

Lithium-ion battery health management has become increasingly important as the application of batt...

Deep Learning-Based Quantitative Assessment of Renal Chronicity Indices in Lupus Nephritis

Background: Renal chronicity indices (CI) have been identified as strong predictors of long-term o...

Exploring CLIP's Dense Knowledge for Weakly Supervised Semantic Segmentation

Weakly Supervised Semantic Segmentation (WSSS) with image-level labels aims to achieve pixel-level...

UWarp: A Whole Slide Image Registration Pipeline to Characterize Scanner-Induced Local Domain Shift

Histopathology slide digitization introduces scanner-induced domain shift that can significantly i...

Contrastive Learning Guided Latent Diffusion Model for Image-to-Image Translation

The diffusion model has demonstrated superior performance in synthesizing diverse and high-quality...

Cross-Modal Prototype Allocation: Unsupervised Slide Representation Learning via Patch-Text Contrast in Computational Pathology

With the rapid advancement of pathology foundation models (FMs), the representation learning of wh...

LPOSS: Label Propagation Over Patches and Pixels for Open-vocabulary Semantic Segmentation

We propose a training-free method for open-vocabulary semantic segmentation using Vision-and-Langu...

ChA-MAEViT: Unifying Channel-Aware Masked Autoencoders and Multi-Channel Vision Transformers for Improved Cross-Channel Learning

Prior work using Masked Autoencoders (MAEs) typically relies on random patch masking based on the ...

Histomorphology-driven multi-instance learning for breast cancer WSI classification

Histomorphology is crucial in breast cancer diagnosis. However, existing whole slide image (WSI) c...

PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Images

Breast cancer survival prediction in computational pathology presents a remarkable challenge due t...

Slide-Level Prompt Learning with Vision Language Models for Few-Shot Multiple Instance Learning in Histopathology

In this paper, we address the challenge of few-shot classification in histopathology whole slide i...

Seeing What Matters: Empowering CLIP with Patch Generation-to-Selection

The CLIP model has demonstrated significant advancements in aligning visual and language modalitie...

Patch-based learning of adaptive Total Variation parameter maps for blind image denoising

We consider a patch-based learning approach defined in terms of neural networks to estimate spatia...

PAPI-Reg: Patch-to-Pixel Solution for Efficient Cross-Modal Registration between LiDAR Point Cloud and Camera Image

The primary requirement for cross-modal data fusion is the precise alignment of data from differen...

Low-Complexity Patch-based No-Reference Point Cloud Quality Metric exploiting Weighted Structure and Texture Features

During the compression, transmission, and rendering of point clouds, various artifacts are introdu...

RETHINED: A New Benchmark and Baseline for Real-Time High-Resolution Image Inpainting On Edge Devices

Existing image inpainting methods have shown impressive completion results for low-resolution imag...

SED-MVS: Segmentation-Driven and Edge-Aligned Deformation Multi-View Stereo with Depth Restoration and Occlusion Constraint

Recently, patch-deformation methods have exhibited significant effectiveness in multi-view stereo ...

Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images

Zero-shot learning holds tremendous potential for histopathology image analysis by enabling models...

Patch-Wise Hypergraph Contrastive Learning with Dual Normal Distribution Weighting for Multi-Domain Stain Transfer

Virtual stain transfer leverages computer-assisted technology to transform the histochemical stain...

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