Results 121 to 130 of about 842,651 (374)

Evolving class for SVM's incremental learning.

, 2007
International audienceThe good generalization performance of support vector machines (SVM) has made them a popular tool in artificial intelligence community.
Benzerrouk, Ahmed, Chebel-Morello, Brigitte, Zerhouni, Noureddine   +2 more
core   +1 more source

RMM: Reinforced Memory Management for Class-Incremental Learning [PDF]

, 2023
Yaoyao Liu, Bernt Schiele, Qianru Sun
openalex   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

Hybrid-Based Machine Incremental Learning in K-Nearest Neighbor Heterogeneous Drifting Environment

Applied Sciences
The ability to continuously learn over time by incorporating new information while holding onto previously acquired expertise is known as incremental learning (IL).
Japheth Otieno Ondiek, Kennedy Odhiambo Ogada, Tobias Mwalili   +2 more
doaj   +1 more source

From Clinic to Computation: Multiscale Bioengineering Strategies for Durable Biological Aortic Valve Replacements

Advanced Functional Materials, EarlyView.
Bioprosthetic aortic valves have revolutionized the treatment of aortic stenosis, but their durability is limited by structural valve deterioration (SVD). This review focuses on the pericardial tissue at the heart of these valves, examining how its mechanical properties and calcification drive fatigue and failure.
Gabriele Greco, Pierfrancesco Gaziano, Serena Anglese, Simone Morganti, Carlo de Vincentiis, Ferdinando Auricchio, Michele Marino, Michele Conti   +7 more
wiley   +1 more source

SLFD: Spatial Location-Aware Feature Distillation for Incremental Object Detection

IEEE Access
In practical applications, object detection models often encounter new classes of interest after initial training. Traditional approaches require retraining from scratch using both existing and new class data—an infeasible process when original ...
Yanyan Shi, Yang Chen, Xinye Yu, Dianxi Shi, Xiaokai Xia   +4 more
doaj   +1 more source

PointMap: A real-time memory-based learning system with on-line and post-training pruning [PDF]

, 2002
Also published in the International Journal of Hybrid Intelligent Systems, Volume 1, January, 2004A memory-based learning system called PointMap is a simple and computationally efficient extension of Condensed Nearest Neighbor that allows the user to ...
Carpenter, Gail, Kopco, Norbert
core   +1 more source

IL2M: Class Incremental Learning With Dual Memory

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019
This paper presents a class incremental learning (IL) method which exploits fine tuning and a dual memory to reduce the negative effect of catastrophic forgetting in image recognition. First, we simplify the current fine tuning based approaches which use a combination of classification and distillation losses to compensate for the limited availability ...
Belouadah, Eden, Popescu, Adrian
openaire   +2 more sources

Additive Manufacturing of NiTi Shape Memory Alloys for Elastocaloric Applications: A Review

Advanced Functional Materials, EarlyView.
Additive manufacturing enables complex NiTi architectures that overcome key limitations in elastocaloric refrigeration, including poor heat transfer and high mechanical work input. This review surveys recent advances in LPBF‐ and DED‐fabricated NiTi shape memory alloys for elastocaloric applications, highlighting process–structure–performance ...
Ignatius Andre Setiawan, Mohammad Mehrali, Jaka Tušek, Shiva Mohajerani, Xiebin Wang, Dermot Brabazon, Mohammad Elahinia, Mehrshad Mehrpouya   +7 more
wiley   +1 more source

Class and Data-Incremental Learning Framework for Baggage Threat Segmentation via Knowledge Distillation

IEEE Access
With air travel growing rapidly worldwide, airports are busier than ever, making efficient security screening a top priority. To meet this growing demand, various advanced X-ray baggage scanners have been deployed at airports worldwide.
Ammara Nasim, Saad Mazhar Khan, Anum Abdul Salam, Arslan Shaukat, Taimur Hassan, Adeel M. Syed, Muhammad Usman Akram   +6 more
doaj   +1 more source