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Found 5 papers, 0 papers with code
Improving Signer Independent Sign Language Recognition for Low Resource Languages
We then evaluate the effect of transfer learning, with different levels of fine-tuning, on the generalisation of signer independent models, and show the effects of different input representations, namely variations in image data and pose estimation.
What's left can't be right -- The remaining positional incompetence of contrastive vision-language models
Contrastive vision-language models like CLIP have been found to lack spatial understanding capabilities.
Towards the extraction of robust sign embeddings for low resource sign language recognition
However, due to a domain mismatch with their training sets and challenging poses in sign language, they lack robustness on sign language data and image-based models often still outperform keypoint-based models.
Deep Context-Aware Novelty Detection
A common assumption of novelty detection is that the distribution of both "normal" and "novel" data are static.
Personalized, Health-Aware Recipe Recommendation: An Ensemble Topic Modeling Based Approach
This paper proposes two different EnsTM based and one Hybrid EnsTM based recommenders.
