Results 101 to 110 of about 762,608 (309)

Teaching Python with team‐based learning: using cloud‐based notebooks for interactive coding education

FEBS Open Bio, EarlyView.
This study presents a novel approach to teaching Python and bioinformatics using team‐based learning and cloud‐hosted notebooks. By integrating interactive coding into biomedical education, the method improves accessibility, student engagement, and confidence—especially for those without a computing background.
Nuno S. Osório, Leonardo D. Garma
wiley   +1 more source

Sparse Compositional Metric Learning

Proceedings of the AAAI Conference on Artificial Intelligence, 2014
We propose a new approach for metric learning by framing it as learning a sparse combination of locally discriminative metrics that are inexpensive to generate from the training data. This flexible framework allows us to naturally derive formulations for global, multi-task and local metric learning. The resulting algorithms have several
Shi, Yuan, Bellet, Aurélien, Sha, Fei
openaire   +3 more sources

Variational Metric Scaling for Metric-Based Meta-Learning

Proceedings of the AAAI Conference on Artificial Intelligence, 2020
Metric-based meta-learning has attracted a lot of attention due to its effectiveness and efficiency in few-shot learning. Recent studies show that metric scaling plays a crucial role in the performance of metric-based meta-learning algorithms. However, there still lacks a principled method for learning the metric scaling parameter automatically.
Fu-Lai Chung, Li-Ming Zhan, Jiaxin Chen, Xiao-Ming Wu   +3 more
openaire   +4 more sources

Diffusion‐based size determination of solute particles: a method adapted for postsynaptic proteins

FEBS Open Bio, EarlyView.
We present a diffusion‐based approach for measuring the size of macromolecules and their complexes, and demonstrate its use on postsynaptic proteins. The method requires fluorescein‐labelled protein samples, a microfluidic device that maintains laminar flow for said samples, a microscope recording the emitted fluorescent signals, and an analytic ...
András László Szabó, Eszter Nagy‐Kanta, Soma Varga, Edit Andrea Jáger, Csaba István Pongor, Mária Laki, András József Laki, Zoltán Gáspári   +7 more
wiley   +1 more source

Deep video-based person re-identification (Deep Vid-ReID): comprehensive survey

EURASIP Journal on Advances in Signal Processing
Person re-identification (ReID) aims to find the person of interest across multiple non-overlapping cameras. It is considered an essential step for person tracking applications which is vital for surveillance.
Rana S. M. Saad, Mona M. Moussa, Nemat S. Abdel-Kader, Hesham Farouk, Samia Mashaly   +4 more
doaj   +1 more source

Report on the 2nd MObility for Vesicle research in Europe (MOVE) symposium—2024

FEBS Open Bio, EarlyView.
The 2nd MObility for Vesicle research in Europe (MOVE) Symposium in Belgrade brought over 280 attendees from 28 countries to advance extracellular vesicle (EV) research. Featuring keynotes, presentations, and industry sessions, it covered EV biogenesis, biomarkers, therapies, and manufacturing.
Dorival Mendes Rodrigues‐Junior, Michaela Kocholata, Marilena E. Lekka, Olga Janouskova, Moran Yadid, Maja Kosanovic   +5 more
wiley   +1 more source

One Model to Rule Them all: A Universal Transformer for Biometric Matching

IEEE Access
This study introduces the first single branch network designed to tackle a spectrum of biometric matching scenarios, including unimodal, multimodal, cross-modal, and missing modality situations.
Madina Abdrakhmanova, Assel Yermekova, Yuliya Barko, Vladislav Ryspayev, Medet Jumadildayev, Huseyin Atakan Varol   +5 more
doaj   +1 more source

Designing and Delivering Effective Faculty Development With the Adult Learner in Mind

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT University faculty are busy professionals tasked with many different responsibilities. While they certainly care about student success, their expertise is generally discipline‐specific and strategies for effective and engaging teaching are developed in the classroom along the way.
Nancy V. Winfrey
wiley   +1 more source

Auto-Weighted Multi-View Discriminative Metric Learning Method With Fisher Discriminative and Global Structure Constraints for Epilepsy EEG Signal Classification

Frontiers in Neuroscience, 2020
Metric learning is a class of efficient algorithms for EEG signal classification problem. Usually, metric learning method deals with EEG signals in the single view space. To exploit the diversity and complementariness of different feature representations,
Jing Xue, Xiaoqing Gu, Tongguang Ni
doaj   +1 more source

Collaborative Metric Learning

Proceedings of the 26th International Conference on World Wide Web, 2017
Metric learning algorithms produce distance metrics that capture the important relationships among data. In this work, we study the connection between metric learning and collaborative filtering. We propose Collaborative Metric Learning (CML) which learns a joint metric space to encode not only users' preferences but also the user-user and item-item ...
Cheng-Kang Hsieh, Tsung-Yi Lin, Yin Cui, Deborah Estrin, Longqi Yang, Serge Belongie   +5 more
openaire   +1 more source