Results 71 to 80 of about 4,930,132 (374)

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Instance Segmentation Network With Self-Distillation for Scene Text Detection

IEEE Access, 2020
Segmentation based methods have become the mainstream for detecting scene text with arbitrary orientations and shapes. In order to address challenging problems such as separating the text instances that are very close to each other, however, these ...
Peng Yang, Guowei Yang, Xun Gong, Pingping Wu, Xu Han, Jiasong Wu, Caisen Chen   +6 more
doaj   +1 more source

Synthetic Nanobiology Actuated Lipometabolic Cell Factory for Autologous Tumor Immunotherapy

Advanced Functional Materials, EarlyView.
FA plays a crucial role in the interaction between tumor cells and the tumor microenvironment, especially for the immune response. A biocatalytic immunoenhancement strategy is developed to boost antitumor immunity by FA metabolic orientation to ceramide. Through the design of this delicate catalytic immunoenhancement strategy, the synthetic nanobiology
Shoujie Zhao, Yejing Zhu, Hengchao Yu, Jun Zhu, Bo Wang, Yu Qiao, Zhimin Tian, Junlong Zhao, Lei Liu   +8 more
wiley   +1 more source

Clean, performance‐robust, and performance‐sensitive historical information based adversarial self‐distillation

IET Computer Vision
Adversarial training suffers from poor effectiveness due to the challenging optimisation of loss with hard labels. To address this issue, adversarial distillation has emerged as a potential solution, encouraging target models to mimic the output of the ...
Shuyi Li, Hongchao Hu, Shumin Huo, Hao Liang   +3 more
doaj   +1 more source

Exploring complementary information of self‐supervised pretext tasks for unsupervised video pre‐training

IET Computer Vision, 2022
This study addresses the problem of the unsupervised pre‐training of video representation learning. The authors' focus is on two common approaches: knowledge distillation and self‐supervised learning.
Wei Zhou, Yi Hou, Kewei Ouyang, Shilin Zhou   +3 more
doaj   +1 more source

Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data [PDF]

, 2022
Corentin Sautier, Gilles Puy, Spyros Gidaris, Alexandre Boulch, Andrei Bursuc, Renaud Marlet   +5 more
openalex   +1 more source

A Unified Self-Distillation Framework for Multimodal Sentiment Analysis with Uncertain Missing Modalities

AAAI Conference on Artificial Intelligence
Multimodal Sentiment Analysis (MSA) has attracted widespread research attention recently. Most MSA studies are based on the assumption of modality completeness. However, many inevitable factors in real-world scenarios lead to uncertain missing modalities,
Mingcheng Li, Dingkang Yang, Yuxuan Lei, Shunli Wang, Shuai Wang, Liuzhen Su, Kun Yang, Yuzheng Wang, Mingyang Sun, Lihua Zhang   +9 more
semanticscholar   +1 more source

Self-Distillation for Further Pre-training of Transformers

, 2023
Pre-training a large transformer model on a massive amount of unlabeled data and fine-tuning it on labeled datasets for diverse downstream tasks has proven to be a successful strategy, for a variety of vision and natural language processing tasks ...
Hwang, Sung Ju, Kang, Minki, Kawaguchi, Kenji, Lee, Juho, Lee, Seanie   +4 more
core  

Using the Photostationary State of Arylazopyrazoles to Control Phase Transitions of Liquid Crystals

Advanced Functional Materials, EarlyView.
A series of new arylazopyrazole photoswitches is designed as dopants for liquid crystalline materials. Unprecedented, the distribution of photoisomers at the photostationary state upon irradiation with light of specific wavelengths (365, 460, 520 nm) is used to control the liquid crystalline phase transitions under isothermal conditions, including ...
Tobias Thiele, Kristina Hrybenko, Christoph Wölper, Michael Giese   +3 more
wiley   +1 more source

Lightweight Person Re-Identification for Edge Computing

IEEE Access
In person re-identification, most prevalent models are predominantly designed for cloud computing environments which introduces complexities that limit their effectiveness in edge computing scenarios.
Wang Jin, Dong Yanbin, Chen Haiming
doaj   +1 more source