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2 days ago · Multimodal tasks require a model to process multiple data modalities (text, image, audio, video) to solve a particular problem.
6 days ago · We propose canonical similarity analysis (CSA), which uses two unimodal encoders to replicate multimodal encoders using limited data. \namemaps unimodal ...
2 days ago · We introduce a deep learning framework for joint registration and segmentation of multi-modal brain images. Under this framework, registration and segmentation ...
2 days ago · A similarity metric is used to assess the degree of similarity between two images connected via a spatial transformation. Hence, it motivates us to design a new ...
7 days ago · CMBF [7] introduces the cross-attention mechanism to co-learn the semantic information of image and text modality, respectively, and then concatenate them.
6 days ago · Overall, there exist three kinds of transfer learning methods to transfer the knowledge of VLMs to the downstream tasks, i.e., full fine-tuning, prompt tuning ...
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6 days ago · Multimodal sarcasm detection leverages multimodal information, such as image, text, etc. to identify special instances whose superficial emotional ...
1 day ago · We perform material classification and grasping prediction tasks by computing the cosine similarity between the embeddings of touch and corresponding text ...
2 days ago · The significant differences in brightness, texture, and structure in whole- brain images of different modalities render similarity measures (e.g.,. Mean Squared ...
2 days ago · Explore advanced techniques for generating questions using multimodal AI, enhancing interaction and understanding across various data types. | Restackio.