Results 81 to 90 of about 28,763 (261)
A miniaturized drug sensitivity and resistance testing (DSRT) workflow based on the Droplet Microarray (DMA) platform enables functional drug testing using minimal patient‐derived tumor material. By screening nanoliter‐scale droplets containing as few as 300 cells, this approach generates reproducible and tumor‐specific drug response profiles ...
Maryam Salarian +7 more
wiley +1 more source
A review on NLP zero-shot and few-shot learning: methods and applications
Zero-shot and few-shot learning techniques in natural language processing (NLP), this comprehensive review traces their evolution from traditional methods to cutting-edge approaches like transfer learning and pre-trained language models, semantic ...
G. Ramesh +6 more
doaj +1 more source
Few-shot cow identification via meta-learning
Cow identification is a prerequisite for precision livestock farming. Biometric-based methods have made significant progress in cow identification. However, substantial labelling costs and frequent identification task changes are still hamper model ...
Xingshi Xu +6 more
doaj +1 more source
Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long +26 more
wiley +1 more source
Ordered three‐dimensional anodic aluminum oxide (3D‐AAO) nanoarchitectures with longitudinal and transverse pores enable architecture‐driven metamaterials. The review maps fabrication advances, including hybrid pulse anodization, and shows how 3D‐AAO templates tailor properties across magnetism, energy, catalysis, and sensing.
Marisol Martín‐González
wiley +1 more source
Learning to learn for few-shot continual active learning
AbstractContinual learning strives to ensure stability in solving previously seen tasks while demonstrating plasticity in a novel domain. Recent advances in continual learning are mostly confined to a supervised learning setting, especially in NLP domain.
Stella Ho +3 more
openaire +2 more sources
Polymorph‐Specific Electronic Transduction in WO3 during Molecular Sensing
Metal‐oxide polymorphs with similar surface chemistry can nevertheless exhibit distinct sensing properties. In γ‐ and ε‐WO3, analyte adsorption appears comparable; yet, only ε‐WO3 induces a pronounced lattice electronic perturbation that accommodates charge in sub‐conduction band minimum states.
Matteo D'Andria +6 more
wiley +1 more source
Template effect and kinetic control enable crystal‐phase engineering of Ru nanocrystals, granting access to either metastable fcc‐Ru or stable hcp‐Ru with distinct surface structures, thermal stabilities, and catalytic behaviors. Moreover, the hcp‐Ru can further serve as an epitaxial template to direct Pd and Rh nanocrystals into the metastable hcp ...
Jianlong He +3 more
wiley +1 more source
Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization
Few-shot learning has achieved great success in recent years, thanks to its requirement of limited number of labeled data. However, most of the state-of-the-art techniques of few-shot learning employ transfer learning, which still requires massive ...
Yukun Liu +5 more
doaj +1 more source
Malware Classification Using Few-Shot Learning Approach
Malware detection, targeting the microarchitecture of processors, has recently come to light as a potentially effective way to improve computer system security.
Khalid Alfarsi +2 more
doaj +1 more source

