Results 271 to 280 of about 1,295,192 (344)

Designing Memristive Materials for Artificial Dynamic Intelligence

Advanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

Predicting Biochemical Recurrence After Robot-Assisted Prostatectomy with Interpretable Machine Learning Model. [PDF]

J Clin Med
Zhang T, Ide H, Lu J, Lu Y, China T, Nagata M, Hachiya T, Horie S.   +7 more
europepmc   +1 more source

Optimising hyperparameters with a tree structured Parzen estimator to improve diabetes prediction. [PDF]

Sci Rep
Munshi RM, Munshi LR, Himdi H, Qashlan A, Munshi R, Alyahyawy OY, Khayyat MM.   +6 more
europepmc   +1 more source

Machine Learning-Based Toothbrushing Region Recognition Using Smart Toothbrush Holder and Wearable Sensors. [PDF]

Biosensors (Basel)
Wang HC, Li JH, Lin YC, Lin CY, Liu CP, Lin TH, Chan CT, Hsieh CY.   +7 more
europepmc   +1 more source

Untargeted Swab Touch Spray-Mass Spectrometry Analysis with Machine Learning for On-Site Breast Surgical Margin Assessment

Laura Min Xuan Chai, Ching Kao, Mingyang Wang, Cheng‐Chih Hsu   +3 more
openalex   +1 more source

Ultrasound radiomics-based machine learning models for risk stratification of follicular thyroid tumors. [PDF]

Front Oncol
Yuan Y, Wang X, Deng H, Cao K, Yu F.
europepmc   +1 more source

Comparative analysis of machine learning algorithms for predicting tibial intramedullary nail length from patient characteristics. [PDF]

J Orthop Traumatol
Hui Y, Hu H, Xiang J, Du X.
europepmc   +1 more source

Seismicity of the south-western South American margin through a machine learning automated approach

Martin Riedel-Hornig, Christian Sippl, Andrés Tassara, Sergio Ruiz, Bertrand Potin, Jorge Antonio Puente Huerta, C E Morales, Favio Carcamo, Catalina Anampa Castro   +8 more
openalex   +1 more source

Maxi–Min Margin Machine: Learning Large Margin Classifiers Locally and Globally [PDF]

IEEE Transactions on Neural Networks, 2008
In this paper, we propose a novel large margin classifier, called the maxi-min margin machine M(4). This model learns the decision boundary both locally and globally. In comparison, other large margin classifiers construct separating hyperplanes only either locally or globally. For example, a state-of-the-art large margin classifier, the support vector
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu   +3 more
semanticscholar   +3 more sources