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Found 14 papers, 4 papers with code
DailyMAE: Towards Pretraining Masked Autoencoders in One Day
Recently, masked image modeling (MIM), an important self-supervised learning (SSL) method, has drawn attention for its effectiveness in learning data representation from unlabeled data.
Reinforcement Learning for Scalable Train Timetable Rescheduling with Graph Representation
Train timetable rescheduling (TTR) aims to promptly restore the original operation of trains after unexpected disturbances or disruptions.
Beyond Accuracy: Statistical Measures and Benchmark for Evaluation of Representation from Self-Supervised Learning
Recently, self-supervised metric learning has raised attention for the potential to learn a generic distance function.
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition
Contrastive learning has achieved great success in skeleton-based action recognition.
Masked Momentum Contrastive Learning for Zero-shot Semantic Understanding
Self-supervised pretraining (SSP) has emerged as a popular technique in machine learning, enabling the extraction of meaningful feature representations without labelled data.
LabelPrompt: Effective Prompt-based Learning for Relation Classification
Specifically, associating natural language words that fill the masked token with semantic relation labels (\textit{e. g.} \textit{``org:founded\_by}'') is difficult.
Finding Point with Image: A Simple and Efficient Method for UAV Self-Localization
To validate the practicality of our framework, we construct a paired dataset, namely UL14, that consists of UAV and satellite views.
NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
To deal with this issue, we advocate a novel lexical enhancement method, InterFormer, that effectively reduces the amount of computational and memory costs by constructing non-flat lattices.
Ranked #9 on
Chinese Named Entity Recognition
on Resume NER
Chinese Named Entity Recognition
named-entity-recognition
+2
Vision-Based UAV Self-Positioning in Low-Altitude Urban Environments
Last, we enhance the Recall@K metric and introduce a new measurement, SDM@K, to evaluate the performance of a trained model from both the retrieval and localization perspectives simultaneously.
MC-SSL0.0: Towards Multi-Concept Self-Supervised Learning
In this aspect the proposed SSL frame-work MC-SSL0. 0 is a step towards Multi-Concept Self-Supervised Learning (MC-SSL) that goes beyond modelling single dominant label in an image to effectively utilise the information from all the concepts present in it.
Attention-based Interpretation and Response to The Trade-Off of Adversarial Training
To boost the robustness of a model against adversarial examples, adversarial training has been regarded as a benchmark method.
MECT: Multi-Metadata Embedding based Cross-Transformer for Chinese Named Entity Recognition
This paper presents a novel Multi-metadata Embedding based Cross-Transformer (MECT) to improve the performance of Chinese NER by fusing the structural information of Chinese characters.
NPT-Loss: A Metric Loss with Implicit Mining for Face Recognition
One key ingredient of DCNN-based FR is the appropriate design of a loss function that ensures discrimination between various identities.
Separable Batch Normalization for Robust Facial Landmark Localization with Cross-protocol Network Training
Different from the standard BN layer that uses all the training data to calculate a single set of parameters, SepBN considers that the samples of a training dataset may belong to different sub-domains.
