Results 181 to 190 of about 41,575 (296)

Unsupervised Deep Learning approach for image registration in Correlative Microscopy for the localization of Nanoparticles [PDF]

BIO Web of Conferences
Daksh Daksh, Kaltbeitzel Anke, Glaßer Gunnar, Lieberwirth Ingo, Landfester Katharina   +4 more
doaj   +1 more source

Navigating polymorph generation and distilled-potential development via entropy-symmetry landscapes for metal plasticity mechanisms. [PDF]

Nat Commun
Li Z, Liu T, Wan X, Zhao S, Zhang Z, Zhou E, Yu W, Zuo Y, Robertson J, Liu S, Guo Y.   +10 more
europepmc   +1 more source

Harnessing Neuron Stability to Improve DNN Verification

Deep Neural Networks (DNN) have emerged as an effective approach to tackling real-world problems. However, like human-written software, DNNs are susceptible to bugs and attacks.
Duong, Hai, Nguyen, ThanhVu, Dwyer, Matthew B., Xu, Dong   +3 more
core  

Enriching historical biologging datasets on seabirds using deep neural networks: A transformer‐based approach to infer energy expenditure proxy from GPS and environmental data

Methods in Ecology and Evolution, EarlyView.
Abstract Recent advances in biologging have led to the widespread use of accelerometers, which generate high‐resolution movement data essential for understanding animal behaviour. Derived from tri‐axial accelerometry, Overall Dynamic Body Acceleration (ODBA) serves as a proxy for energy expenditure that is less invasive and more cost‐effective than ...
Noémie Muquet, Adrien Brunel, Christophe Barbraud, Leandro Bugoni, Karine Delord, Guilherme Tavares Nunes, Jean‐Daniel Zucker, Sophie Lanco   +7 more
wiley   +1 more source

Inferring processes within dynamic forest models using hybrid modelling

Methods in Ecology and Evolution, EarlyView.
Abstract Modelling forest dynamics under novel climatic conditions requires a careful balance between process‐based understanding and empirical flexibility. Dynamic vegetation models (DVM) represent ecological processes mechanistically, but their performance is sensitive to misspecified functional forms and to unavoidable structural simplifications ...
Maximilian Pichler, Yannek Käber
wiley   +1 more source

Optimization of speech emotion recognition using hybrid dataset integration and deep learning-based feature fusion with a novel balanced focal entropy loss. [PDF]

Sci Rep
Nagro S.
europepmc   +1 more source

Too good to be true: Synthetic AI faces are more average than real faces and super‐recognizers know it

British Journal of Psychology, EarlyView.
Abstract The AI revolution has produced synthetic faces that often appear more human than photos of real people. We tested whether individual differences in human face recognition ability explain variation in discriminating AI from real faces. Super‐recognizers – people with exceptional ability to recognize human faces (N = 36) – outperformed a typical
James D. Dunn, David White, Clare A. M. Sutherland, Elizabeth J. Miller, Ben A. Steward, Amy Dawel   +5 more
wiley   +1 more source

A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study. [PDF]

JMIR Mhealth Uhealth
Rantula OA, Lipponen JA, Halonen J, Jäntti H, Rissanen TT, Tarvainen MP, Naukkarinen NS, Seljola ES, Santala OE, Sedha J, Martikainen TJ, Hartikainen JEK.   +11 more
europepmc   +1 more source

A Survey of Methods for Constructing 3D Urban Models From Point Clouds

Computer Graphics Forum, EarlyView.
The survey outlines a general process for constructing 3D models from point clouds and categorizes the methods based on their use of templates, basic surface primitives, hybrid approaches, or linear primitives. Additionally, the survey reviews the datasets and benchmarks that are essential for testing and training the developed methods.
Chiara Romanengo, Silvia Biasotti, Bianca Falcidieno, Daniela Cabiddu, Elia Moscoso Thompson, Michela Spagnuolo   +5 more
wiley   +1 more source

Automated echocardiographic detection of mitral valve prolapse and mitral regurgitation with video-based artificial intelligence algorithms. [PDF]

Eur Heart J Digit Health
Ansari MU, Barrios JP, Tastet L, Jhawar R, Cristin L, Rich A, Bibby D, Fang Q, Arya F, Crudo V, Nguyen T, Shah DJ, Delling FN, Tison GH.   +13 more
europepmc   +1 more source