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Deep Learning with Yacine on MSN4d
20 Activation Functions in Python for Deep Neural Networks | ELU, ReLU, Leaky ReLU, Sigmoid, Cosine
Explore 20 essential activation functions implemented in Python for deep neural networks—including ELU, ReLU, Leaky ReLU, ...
IEEE28d
Weak–Strong Graph Contrastive Learning Neural Network for Hyperspectral Image Classification
Abstract: Deep learning methods have shown promising ... To address the issues, we propose WSGraphCL, a weak-strong graph CL model for HSI classification, and conduct experiments in a few-shot ...
techxplore20d
Deep learning model dramatically improves subgraph matching accuracy by eliminating noise
A research team from Kumamoto University has developed a promising deep learning model that significantly ... alignment between query and data graphs. Shared-graph convolution, a new convolution ...
National Geographic news14d
National Geographic Your Shot
Welcome to Nat Geo Your Shot: National Geographic’s global community for aspiring visual storytellers. Find the community on Instagram @NatGeoYourShot and follow along for hashtag challenges ...
IEEE28d
Cross-Modality Domain Adaptation Based on Semantic Graph Learning: From Optical to SAR Images
which results in low-quality pseudolabel assignment for SAR images. To address the above issue, we propose a semantic graph learning framework (SGLF) to comprehensively align the global features of ...
C&EN24d
Integrating Machine Learning-Based Pose Sampling with Established Scoring Functions for Virtual Screening
Department of Pharmaceutical Sciences, Division of Pharmaceutical Chemistry, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria Christian Doppler Laboratory ...
BMJ26d
Machine learning model for differentiating malignant from benign thyroid nodules based on the thyroid function data
1 Department of Integrated Traditional and Western Medicine,The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China Objectives To ...
C&EN26d
Machine Learning Prediction of Optical Properties of Coumarin Derivatives Using Gaussian-Weighted Graph Convolution and Subgraph Modular Input
Department of Chemistry and Research Institute for Natural Science, Korea University, Seoul 02841, Korea ...