Results 81 to 90 of about 10,284,296 (292)
Prototype Completion for Few-Shot Learning
Few-shot learning aims to recognize novel classes with few examples. Pre-training based methods effectively tackle the problem by pre-training a feature extractor and then fine-tuning it through the nearest centroid based meta-learning. However, results show that the fine-tuning step makes marginal improvements.
Baoquan Zhang +3 more
openaire +4 more sources
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source
Few-Shot Learning for Biometric Verification
In machine learning applications, it is common practice to feed as much information as possible. In most cases, the model can handle large data sets that allow to predict more accurately. In the presence of data scarcity, a Few-Shot learning (FSL) approach aims to build more accurate algorithms with limited training data.
Umaid M. Zaffar +3 more
openaire +3 more sources
Incremental Few Shot Learning across Datasets
Graduate School of Artificial IntelligenceTo mimic the human being's intellectual characteristics, modern deep learning algorithms focus on two goals: adapting the new knowledge with few samples and recognizing both old and new knowledge as much as ...
Park, Joon Sung
core
Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns
Objective Rheumatoid arthritis is a heterogeneous disease. Data‐driven approaches, from synovial histology to joint involvement patterns (JIPs), have sought to define clinically meaningful subgroups. Whether these subgroups represent stable phenotypes or transient disease states remains unclear.
Tjardo Maarseveen +24 more
wiley +1 more source
Edible Cuttlefish Ink: Complex Chemistry, Structure, and Electrical Response
An integrated approach of chemistry‐structure‐electrical properties is used to assess the potential of edible cuttlefish ink as a bio‐based conductive ink for printable electronics. Chromatography and Neutron Activation Analysis reveal a fascinating molecular and elemental diversity.
Camille Bour‐Cardinal +5 more
wiley +1 more source
Interval Bound Interpolation for Few-shot Learning with Few Tasks [PDF]
Few-shot learning aims to transfer the knowledge acquired from training on a diverse set of tasks to unseen tasks from the same task distribution with a limited amount of labeled data.
Chakrabarty, Anish +3 more
core +1 more source
Ferroelectric tunnel junction devices based on epitaxial undoped ferroelectric HfO2 films demonstrate stable switching endurance of over 106 switching cycles, low write voltages of ±3 V, 16 measured resistance states, and neuromorphic capability.
Markus Hellenbrand +13 more
wiley +1 more source
Relational Generalized Few-Shot Learning
Transferring learned models to novel tasks is a challenging problem, particularly if only very few labeled examples are available. Although this few-shot learning setup has received a lot of attention recently, most proposed methods focus on discriminating novel classes only.
Xiahan Shi +4 more
openaire +3 more sources
Kinetics‐Controlled Architecture of Binder‐Free Organic Electrodes for Enhanced Ion Transport
Pulse reverse electrodeposition controls nucleation and growth to create hierarchically porous Py‐derived oligomeric electrodes with enhanced ionic accessibility and reduced transport resistance. The resulting binder‐free architectures translate these transport advantages into practical sodium‐storage functionality.
Satendra Kumar +1 more
wiley +1 more source

