all AI news
Incremental Prototype Tuning for Class Incremental Learning. (arXiv:2204.03410v6 [cs.CV] UPDATED)
Aug. 17, 2022, 1:12 a.m. | Jieren Deng, Jianhua Hu, Haojian Zhang, Yunkuan Wang
cs.CV updates on arXiv.org arxiv.org
Class incremental learning(CIL) has attracted much attention, but most
existing related works focus on fine-tuning the entire representation model,
which inevitably results in much catastrophic forgetting. In the contrast, with
a semantic-rich pre-trained representation model, parameter-additional-tuning
(PAT) only changes very few parameters to learn new visual concepts. Recent
studies have proved that PAT-based CIL can naturally avoid fighting against
forgetting by replaying or distilling like most of the existing methods.
However, we find that PAT-based CIL still faces serious semantic …
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Senior ML Researcher - 3D Geometry Processing | 3D Shape Generation | 3D Mesh Data
@ Promaton | Europe
Cleared Senior Software Engineer, Computer Vision, Federal
@ CCRi | Chantilly, Virginia, United States
Data Analyst - B2C
@ DAZN | Hyderabad, India
Product Marketing Manager - AI Chatbot
@ SendBird | San Mateo, California, United States
Alternance Alternant Ingénieur Développement logiciel temps réel embarqué / computer vision (F/H)
@ Alstom | Villeurbanne, FR
AOT Data Analyst II - Highway Project Delivery
@ State of Vermont | Barre, VT, US