Shot Classification

Shot classification, particularly few-shot classification, focuses on training classifiers with limited labeled data, aiming to improve generalization to unseen classes. Current research emphasizes adapting pre-trained models like CLIP, employing meta-learning algorithms, and exploring techniques such as prompt engineering and hyperdimensional computing to enhance efficiency and accuracy. This field is crucial for addressing data scarcity issues in various domains, including medical imaging and natural language processing, enabling the development of more robust and adaptable AI systems.

Papers

August 26, 2022

Few-Shot Learning Meets Transformer: Unified Query-Support Transformers for Few-Shot Classification
Xixi Wang, Xiao Wang, Bo Jiang, Bin Luo
LeArning Abstract Classification Code Transformer Based Shot Learning Shot Classification Patch Transformer Query Transformer

August 25, 2022

Image augmentation improves few-shot classification performance in plant disease recognition
Frank Xiao
Convolutional Neural Network Transfer Learning Shot Classification Data Augmentation Technique Image Augmentation Plant Disease

August 23, 2022

FS-BAN: Born-Again Networks for Domain Generalization Few-Shot Classification
Yunqing Zhao, Ngai-Man Cheung
Classification Code Domain Generalization Domain Shift Generalization Performance Shot Classification Improved Generalization Shot Generalization

August 22, 2022

Transductive Decoupled Variational Inference for Few-Shot Classification
Anuj Singh, Hadi Jamali-Rad
Classification Code Shot Learning Variational Inference Shot Classification Shot Task TinyImagenet Benchmark

August 18, 2022

Active PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Training
Xia Zeng, Arkaitz Zubiaga
Fact Checking Shot Classification Shot Fake News Detection Active Annotation Pattern Exploiting Training

August 15, 2022

Hierarchical Attention Network for Few-Shot Object Detection via Meta-Contrastive Learning
Dongwoo Park, Jong-Min Lee
Contrastive Learning Shot Classification Shot Object Detection Hierarchical Attention Large Receptive Field Contrastive Meta Learning

August 5, 2022

Convolutional Ensembling based Few-Shot Defect Detection Technique
Soumyajit Karmakar, Abeer Banerjee, Prashant Sadashiv Gidde, Sumeet Saurav, Sanjay Singh
Shot Learning Shot Classification Defect Detection Model Ensembling Pre Trained Convolutional Neural Network Shot Approach

July 24, 2022

Kernel Relative-prototype Spectral Filtering for Few-shot Learning
Tao Zhang, Wu Huang
Shot Learning Shot Classification Kernel Hilbert Space Spectral Filtering

July 19, 2022

Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification
Renrui Zhang, Zhang Wei, Rongyao Fang, Peng Gao, Kunchang Li, Jifeng Dai, Yu Qiao, Hongsheng Li
Zero Shot Single CLIP Shot Classification Contrastive Vision Language Tip Adapter

July 6, 2022

FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments
Jishnu Jaykumar P, Yu-Wei Chao, Yu Xiang
Data Set Shot Learning Object Recognition Shot Classification Object Representation Shot Object Detection Robot Environment

July 3, 2022

Dynamic Sub-Cluster-Aware Network for Few-Shot Skin Disease Classification
Shuhan LI, Xiaomeng Li, Xiaowei Xu, Kwang-Ting Cheng
Shot Learning Shot Classification Skin Lesion Clustering Friendly Representation

June 16, 2022

Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification
Xueliang Wang, Jianyu Cai, Shuiwang Ji, Houqiang Li, Feng Wu, Jie Wang
Shot Classification Label Augmentation Adaptive Metric Semi Supervised Few Shot

May 31, 2022

FHIST: A Benchmark for Few-shot Classification of Histological Images
Fereshteh Shakeri, Malik Boudiaf, Sina Mohammadi, Ivaxi Sheth, Mohammad Havaei, Ismail Ben Ayed, Samira Ebrahimi Kahou
New Benchmark Image Classification Shot Learning Histopathological Image Shot Classification

May 20, 2022

Prototypical Calibration for Few-shot Learning of Language Models
Zhixiong Han, Yaru Hao, Li Dong, Yutao Sun, Furu Wei
Language Model Context Learning Shot Classification Different Cluster Robust Decision Prototypical Calibration

May 11, 2022

Making Pretrained Language Models Good Long-tailed Learners
Chen Zhang, Lei Ren, Jingang Wang, Wei Wu, Dawei Song
Prompt Tuning Shot Classification Large Pre Trained Language Model Long Tailed Learning Long Tailed Classification

May 5, 2022

April 26, 2022

Meta-free few-shot learning via representation learning with weight averaging
Kuilin Chen, Chi-Guhn Lee
Transfer Learning Shot Learning Individual Representation Shot Classification Meta Level WEight AVERaging Shot Learning Benchmark

April 9, 2022

Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification
Jiangtao Xie, Fei Long, Jiaming Lv, Qilong Wang, Peihua Li
Classification Code Shot Classification Deep Representation Joint Distribution Shot Classifier

April 7, 2022

Few-Shot Forecasting of Time-Series with Heterogeneous Channels
Lukas Brinkmeyer, Rafael Rego Drumond, Johannes Burchert, Lars Schmidt-Thieme
Time Series Time Series Forecasting Multivariate Time Series State of the Art Forecasting Shot Classification Heterogeneous Wireless Shot Forecasting