Results 191 to 200 of about 4,404,768 (300)

Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits [PDF]

We consider the problem of late multi-modal fusion for discriminative learning. Motivated by noisy, multi-source domains that require understanding the reliability of each data source, we explore the notion of credibility in the context of multi-modal ...
Kersting, Kristian, Natarajan, Sriraam, Mathur, Saurabh, Sidheekh, Sahil, Blasch, Erik, Tenali, Pranuthi   +5 more
core  

A perioperative multi-modal fusion and deep learning-based prognostic system for upper tract urothelial carcinoma: a multi-institutional study. [PDF]

Insights Imaging
Peng X, Li Y, Shi W, Xiao B, Xiao X, Yue X, Xv Q, Jiang Q, He W, Xv Y, Xiao M.   +10 more
europepmc   +1 more source

A Multi-Modal Fusion Method Based on Higher-Order Orthogonal Iteration Decomposition. [PDF]

Entropy (Basel), 2021
Liu F, Chen J, Tan W, Cai C.
europepmc   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Robust Rear-View Human Tracking for Robotic Visual Sensing: A Spatiotemporal Prediction and Multi-Modal Fusion Approach. [PDF]

Sensors (Basel)
Jia X, Xie J, Li Y, Liang J, Zhang Z.
europepmc   +1 more source

Swin-MFA: A Multi-Modal Fusion Attention Network Based on Swin-Transformer for Low-Light Image Human Segmentation. [PDF]

Sensors (Basel), 2022
Yi X, Zhang H, Wang Y, Guo S, Wu J, Fan C.   +5 more
europepmc   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Multi-Modal Fusion Frameworks of Subgraph-Optimized Graph Autoencoder for Molecular Property Prediction. [PDF]

J Chem Inf Model
Zhang K, Han C, Zhang F, Lin C, Li Q, Zang T, Zhao Y.   +6 more
europepmc   +1 more source

Multi-Modal Fusion Emotion Recognition Method of Speech Expression Based on Deep Learning. [PDF]

Front Neurorobot, 2021
Liu D, Wang Z, Wang L, Chen L.
europepmc   +1 more source

Pulsed Laser‐Assisted Phase Engineering of Multimetallic Colloidal Nanocrystals With Complex Compositions

Advanced Materials, EarlyView.
The engineering of colloidal nanocrystals with complex compositions has emerged as a highly active area of research within nanomaterials science. This review covers key aspects of colloidal solid‐solution nanocrystal formation using pulsed laser irradiation.
Marina T. Candela, Sergio Triviño‐Sánchez, Andrés Guerrero‐Martínez, Luis M. Liz‐Marzán, Guillermo González‐Rubio   +4 more
wiley   +1 more source