8 papers
Few-Shot Domain Incremental Learning via Continual Vision-Language Consolidation
Naeem Paeedeh, Mahardhika Pratama, Wolfgang Mayer +3
Existing domain-incremental learning (DIL) strategies call for massive amounts of data to adapt to new domains and suffer from the overfitting problem in the case of data scarcity.…
Cross-Domain Few-Shot Learning for Hyperspectral Image Classification Based on Mixup Foundation Model
Naeem Paeedeh, Mahardhika Pratama, Ary Shiddiqi +3
Although cross-domain few-shot learning (CDFSL) for hyper-spectral image (HSI) classification has attracted significant research interest, existing works often rely on an unrealist…
DualPrompt-MedCap: A Dual-Prompt Enhanced Approach for Medical Image Captioning
Yining Zhao, Ali Braytee, Mukesh Prasad
Medical image captioning via vision-language models has shown promising potential for clinical diagnosis assistance. However, generating contextually relevant descriptions with acc…
AeroLite: Tag-Guided Lightweight Generation of Aerial Image Captions
Xing Zi, Tengjun Ni, Xianjing Fan +4
Accurate and automated captioning of aerial imagery is crucial for applications like environmental monitoring, urban planning, and disaster management. However, this task remains c…
Vision Transformers with Autoencoders and Explainable AI for Cancer Patient Risk Stratification Using Whole Slide Imaging
Ahmad Hussein, Mukesh Prasad, Ali Anaissi +1
Cancer remains one of the leading causes of mortality worldwide, necessitating accurate diagnosis and prognosis. Whole Slide Imaging (WSI) has become an integral part of clinical w…
Enhancing Sentiment Analysis through Multimodal Fusion: A BERT-DINOv2 Approach
Taoxu Zhao, Meisi Li, Kehao Chen +6
Multimodal sentiment analysis enhances conventional sentiment analysis, which traditionally relies solely on text, by incorporating information from different modalities such as im…