Miscellaneous
20 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Miscellaneous
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BIG-bench
Most implemented papers
Deep Face Recognition: A Survey
Deep learning applies multiple processing layers to learn representations of data with multiple levels of feature extraction.
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
Joint Statistical and Causal Feature Modulated Face Anti-Spoofing
In this paper, we propose a hierarchical feature modulation (HFM) approach for stable face anti-spoofing in unseen domains and unseen attacks.
eXclusive Autoencoder (XAE) for Nucleus Detection and Classification on Hematoxylin and Eosin (H&E) Stained Histopathological Images
huangch/xae4hne
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We also proposed an algorithm for lymphocyte segmentation based on nucleus detection and classification.
A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
In order to accelerate the clinical usage of biomedical image analysis based on deep learning techniques, we intentionally expand this survey to include the explanation methods for deep models that are important to clinical decision making.
IRNet: Instance Relation Network for Overlapping Cervical Cell Segmentation
2023-MindSpore-1/ms-code-214
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In this paper, we propose a novel Instance Relation Network (IRNet) for robust overlapping cell segmentation by exploring instance relation interaction.
Asymmetric Co-Teaching for Unsupervised Cross Domain Person Re-Identification
FlyingRoastDuck/ACT_AAAI20
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This procedure encourages that the selected training samples can be both clean and miscellaneous, and that the two models can promote each other iteratively.
Targeted VAE: Variational and Targeted Learning for Causal Inference
matthewvowels1/TVAE_release
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Undertaking causal inference with observational data is incredibly useful across a wide range of tasks including the development of medical treatments, advertisements and marketing, and policy making.
CE-FPN: Enhancing Channel Information for Object Detection
RooKichenn/CEFPN
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Instead of the original 1x1 convolution and linear upsampling, it mitigates the information loss due to channel reduction.
Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition
shuaiwa16/OtherClassNER
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ACL 2021
Few-shot Named Entity Recognition (NER) exploits only a handful of annotations to identify and classify named entity mentions.
