Exploring the Visual Shortcomings of Multimodal LLMs中的一些分析结果,可以看到大部分Late-Fusion的MLLM模型在一些简单的物体位置,物体关系都难以区分开,如右下图所示,而Early Fusion的代表模型Gemini Pro的表现相对更好一些;这种MLLM模型的视觉缺陷类似于LLM模型有时候不能区分9.1和9.82哪个数大,属于人类非常好区分但...
Three different operators (Concatenation, Sum, and Max) were employed to fuse mid-level multimodal video features, using the fused data representations as input for the TVSS task. We analyzed the operators' accuracy with those from current fusion approaches based on correlation detection and deep ...
2023 IEEE International Conference on E-health Networking, Application & Services (Healthcom 2023)Diagnosing Alzheimer’s Disease using Early-LateMultimodal Data Fusion with Jacobian MapsYasmine Mustafa, Tie Luo ∗Computer Science Department, Missouri University of Science and Technology, USAEmail: {...
The Hermite transform is introduced as an image representation model that can be used to tackle the problem of fusion in multimodal medical imagery. This m... B Escalante-Ramírez - 《Computers & Electrical Engineering》 被引量: 48发表: 2008年 Log-Gabor Energy Based Multimodal Medical Image Fu...
Surprisingly, we observe that: (1) multimodal prompts and (2) vision-language models with early fusion (e.g., BEIT-3) are beneficial for prompting SAM for accurate referring segmentation. Our experiments show that the proposed EVF-SAM based on BEIT-3 can obtain state-of-the-art performance...
Surprisingly, we observe that: (1) multimodal prompts and (2) vision-language models with early fusion (e.g., BEIT-3) are beneficial for prompting SAM for accurate referring segmentation. Our experiments show that the proposed EVF-SAM based on BEIT-3 can obtain state-of-the-art performance...
Then, the complex multimodal relations were explored by the gated attention fusion module to obtain the fused bimodal features. Finally, the fused vectors were input into a fully connected neural network to realize PD predictive classification. Experiments showed that the PIDGN framework could ...
(1991). Development of intersensory function: Age-related differences in stimulus selection of multimodal compounds in rats as revealed by Pavlovian conditioning. Journal of Experimental Psychology: Animal Behavior Processes, 17(4), 448–464. PubMed Google Scholar Nettle, D., & Bateson, M. (...
Interpretable multimodal fusion networks reveal mechanisms of brain cognition IEEE Trans. Med. Imag., 40 (5) (2021), pp. 1474-1483 CrossrefView in ScopusGoogle Scholar [53] J. Lynch, D. Hawkes, J. Buckland-Wright Analysis of texture in macro-radiographs of osteoarthritic knees, using the ...
In this study, we use DL models to perform multimodal data fusion (Fig. 3) (i.e. imaging, EHR and genomic SNP data) for classifying patients into CN, MCI, and AD groups. We use stacked de-noising auto-encoders for EHR and SNP, and 3D convolutional neural networks (CNNs) for MRI ...