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Found 10 papers, 8 papers with code
Medical Unlearnable Examples: Securing Medical Data from Unauthorized Traning via Sparsity-Aware Local Masking
With the rapid growth of artificial intelligence (AI) in healthcare, there has been a significant increase in the generation and storage of sensitive medical data.
Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models
Sora is a text-to-video generative AI model, released by OpenAI in February 2024.
Multimodal ChatGPT for Medical Applications: an Experimental Study of GPT-4V
In this paper, we critically evaluate the capabilities of the state-of-the-art multimodal large language model, i. e., GPT-4 with Vision (GPT-4V), on Visual Question Answering (VQA) task.
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation
The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation tasks.
SAMAug: Point Prompt Augmentation for Segment Anything Model
Starting with an initial point prompt, SAM produces an initial mask, which is then fed into our proposed SAMAug to generate augmented point prompts.
BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks
Conventional task- and modality-specific artificial intelligence (AI) models are inflexible in real-world deployment and maintenance for biomedicine.
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Learning to Generate Poetic Chinese Landscape Painting with Calligraphy
In this paper, we present a novel system (denoted as Polaca) to generate poetic Chinese landscape painting with calligraphy.
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
The goal of AIGC is to make the content creation process more efficient and accessible, allowing for the production of high-quality content at a faster pace.
CellMix: A General Instance Relationship based Method for Data Augmentation Towards Pathology Image Classification
In pathology image analysis, obtaining and maintaining high-quality annotated samples is an extremely labor-intensive task.
Shuffle Instances-based Vision Transformer for Pancreatic Cancer ROSE Image Classification
The rapid on-site evaluation (ROSE) technique can signifi-cantly accelerate the diagnosis of pancreatic cancer by im-mediately analyzing the fast-stained cytopathological images.
