TSVFN: Two-Stage Visual Fusion Network for multimodal relation extraction 2023, Information Processing and Management Show abstract MTGCN: A multi-task approach for node classification and link prediction in graph data 2022, Information Processing and Management Citation Excerpt : Its purpose is to use...
Federated Continual Learning for Edge-AI: A Comprehensive Survey 2024 Arxiv Continual Learning with Neuromorphic Computing: Theories, Methods, and Applications 2024 Arxiv Recent Advances of Multimodal Continual Learning: A Comprehensive Survey 2024 Arxiv Towards General Industrial Intelligence: A Survey on...
A Multimodal Feature Representation Model for Transfer-Learning-Based Identification of Imagesdoi:10.1007/s40009-024-01402-7NaturalSyntheticLSTMGRUEHOCNNDigital image classification assists in distinguishing natural and synthetic images to detect computer-generated objects. However, CGI improvements make it ...
A deep learning-based hierarchical approach is proposed for both unimodal and multimodal SER systems in this work. Of these, the audio-based unimodal system proposes using a combination of 33 features, which include prosody, spectral, and voice quality-based audio features. Further, for the ...
✨✨✨ Behold our meticulously curated trove of Multimodal Large Language Models (MLLM) resources! 📚🔍 Feast your eyes on an assortment of datasets, techniques for tuning multimodal instructions, methods for multimodal in-context learning, approaches for multimodal chain-of-thought, visual re...
adept at modeling the global aspects of EEG signals and employing attention mechanisms for precise classification. We also present an innovative algorithm for data mapping in transfer learning, ensuring consistent feature representation across both spatio-temporal dimensions. This approach significantly improve...
Single-cell multimodal sequencing technologies are developed to simultaneously profile different modalities of data in the same cell. It provides a unique opportunity to jointly analyze multimodal data at the single-cell level for the identification of distinct cell types. A correct clustering result is...
In this post, we discuss what multimodals are, how they work, and their impact on solving computer vision problems.
Unlearning Backdoor Threats: Enhancing Backdoor Defense in Multimodal Contrastive Learning via Local Token Unlearning 2024 Liang et al. arXiv UBT - ∇τ: Gradient-based and Task-Agnostic machine Unlearning 2024 Trippa et al. arXiv - - Towards Independence Criterion in Machine Unlearning of Fea...
Analyzing customized bus service on a multimodal travel corridor: An analytical modeling approach J. Transport. Eng., Part A: Syst., 143 (11) (2017), p. 04017057 CrossrefGoogle Scholar Zhang et al., 2005 W. Zhang, H. Gu, R.K. Raphael The impacts of SARS on the consumer behaviour of...