Latest AI and machine learning research in covid-19 for healthcare professionals.
As a common image editing operation, image composition involves integrating foreground objects into background scenes. In this paper, we expand the application of the concept of Affordance from human-centered image composition tasks to a more general object-scene composition framework, addressing the complex interplay between foreground objects and background scenes. Following the principle of A...
Advancements in multimodal Large Language Models (LLMs), such as OpenAI's GPT-4o, offer significant potential for mediating human interactions across various contexts. However, their use in areas such as persuasion, influence, and recruitment raises ethical and security concerns. To evaluate these models ethically in public influence and persuasion scenarios, we developed a prompting strategy us...
The adaptive immune system holds invaluable information on past and present immune responses in the form of B and TÂ cell receptor sequences, but we ar...
Determining the specificity of adaptive immune receptors-B cell receptors (BCRs), their secreted form antibodies, and TÂ cell receptors (TCRs)-is criti...
Recently, diffusion models have emerged as promising newcomers in the field of generative models, shining brightly in image generation. However, whe...
The iterative bleaching extends multiplexity (IBEX) Knowledge-Base is a central portal for researchers adopting IBEX and related 2D and 3D immunoflu...
Event-based semantic segmentation has great potential in autonomous driving and robotics due to the advantages of event cameras, such as high dynami...
Sentiment analysis is an essential component of natural language processing, used to analyze sentiments, attitudes, and emotional tones in various c...
The Multimodal Learning Workshop (PBVS 2024) aims to improve the performance of automatic target recognition (ATR) systems by leveraging both Synthe...
Image Splicing Localization (ISL) is a fundamental yet challenging task in digital forensics. Although current approaches have achieved promising pe...
We empirically study the scaling properties of various Diffusion Transformers (DiTs) for text-to-image generation by performing extensive and rigoro...
Domain Generalized Semantic Segmentation (DGSS) seeks to utilize source domain data exclusively to enhance the generalization of semantic segmentati...
Unsupervised visual anomaly detection is crucial for enhancing industrial production quality and efficiency. Among unsupervised methods, reconstruct...
The Mapper algorithm is an essential tool for visualizing complex, high dimensional data in topology data analysis (TDA) and has been widely used in...
Open-vocabulary image segmentation has been advanced through the synergy between mask generators and vision-language models like Contrastive Languag...
Reconstructing three-dimensional (3D) scenes with semantic understanding is vital in many robotic applications. Robots need to identify which object...
Prostate cancer is a leading cause of cancer-related deaths among men. The recent development of high frequency, micro-ultrasound imaging offers imp...
Large Language Model (LLM)-Powered Conversational Agents have the potential to provide users with scaled behavioral healthcare support, and potentia...
Significant disparities between the features of natural images and those inherent to histopathological images make it challenging to directly apply ...
Image editing has advanced significantly with the development of diffusion models using both inversion-based and instruction-based methods. However,...