Latest AI and machine learning research in smoking & tobacco for healthcare professionals.
Raw images preserve linear sensor measurements and high bit-depth information crucial for advanced v...
This demonstration presents Digital-Physical Adversarial Attacks (DiPA), a new class of practical ad...
Self-supervised Vision Transformers (ViTs) like DINO show an emergent ability to discover objects, t...
Computational pathology relies on effective representation learning to support cancer research and p...
Random cropping is one of the most common data augmentation techniques in computer vision, yet the r...
Self-supervised learning has emerged as a powerful paradigm for learning visual representations with...
Whole Slide Images (WSIs) exhibit hierarchical structure, where diagnostic information emerges from ...
Whole Slide Images (WSIs) exhibit hierarchical structure, where diagnostic information emerges from ...
Although infrared pedestrian detectors have been widely deployed in visual perception tasks, their v...
Multiple Instance Learning (MIL) is the predominant framework for classifying gigapixel whole-slide ...
Estimating slide- and patch-level gene expression profiles from pathology images enables rapid and l...
Sleep disturbances are tightly linked to cardiovascular risk, yet polysomnography (PSG)-the clinical...
Recent adapter-based CLIP tuning (e.g., Tip-Adapter) is a strong few-shot learner, achieving efficie...
Background: Plants produce diverse metabolites with potential benefits for human health. However, th...
Recent advancements in diffusion-based image editing pose a significant threat to the authenticity o...
Image Deepfake Detection (IDD) separates manipulated images from authentic ones by spotting artifact...
Facial identification systems are increasingly deployed in surveillance and yet their vulnerability ...
Adversarial patches are physically realizable localized noise, which are able to hijack Vision Trans...
A recent cutting-edge topic in multimodal modeling is to unify visual comprehension and generation w...
Generative models are widely employed to enhance the photorealism of synthetic data for training com...
Objective: To evaluate the effectiveness of various Large Language Models (LLMs) in identifying reli...