A simple yet effective post-processing method for detecting unknown intent in dialogue systems based on pre-trained deep neural network classifiers
-
Updated
Apr 25, 2019 - Python
A simple yet effective post-processing method for detecting unknown intent in dialogue systems based on pre-trained deep neural network classifiers
Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates
Code for Paper: Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
Deep Unknown Intent Detection with Margin Loss (ACL2019)
"OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning" by Mamshad Nayeem Rizve, Navid Kardan, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah (ECCV 2022)
Python code for detecting and learning new classes of threats present in crops
Official PyTorch implementation of ODISE: Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models [CVPR 2023 Highlight]
AirObject: A Temporally Evolving Graph Embedding for Object Identification (CVPR 2022)
Papers for Open Knowledge Discovery
(ICCV 2023) Parametric Classification for Generalized Category Discovery: A Baseline Study
Code for our CVPR 2024 paper "Active Generalized Category Discovery"
Add a description, image, and links to the open-world-classification topic page so that developers can more easily learn about it.
To associate your repository with the open-world-classification topic, visit your repo's landing page and select "manage topics."