arXiv:2101.06025
공식 코드 · Papers with Code
Motion-Based Handwriting Recognition and Word Reconstruction
원문 초록
In this project, we leverage a trained single-letter classifier to predict the written word from a continuously written word sequence, by designing a word reconstruction pipeline consisting of a dynamic-programming algorithm and an auto-correction model. We conduct experiments to optimize models in this pipeline, then employ domain adaptation to explore using this pipeline on unseen data distributions.
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Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation
UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions
Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud Recognition
Unlocking Constraints: Source-Free Occlusion-Aware Seamless Segmentation
Efficient and Generalizable Speaker Diarization via Structured Pruning of Self-Supervised Models
Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization
토론
이 논문과 연결된 포럼 글이 아직 없습니다.