eLife

Unbend: Correction of local beam-induced sample motion in cryo-EM images using a 3D spline model

This paper describes Unbend - a new method for measuring and correcting motions in cryo-EM images, with a particular emphasis on more challenging in situ samples such as lamella and whole cells. The ...
GitHub

SVMClassifier-Linear Kernel - 3 class classification data

here , Linear kernel does hard classification, but OVR.predict uses score() method and does plattScaling. Please do let me know what is the possible issue here. How to get prediction result from this ...
Scientific Research Publishing

An Evaluation of Machine Learning Models for Threat Classification in IoT Devices ()

1 Center for Cyberspace Studies, Nasarawa State University, Keffi, Nigeria. 2 Department of Computer Engineering, Nile University of Nigeria, Abuja, Nigeria. 3 Department of Public and International ...
NBC Los Angeles

OpenAI says newest AI model can ‘think with images,' understanding diagrams and sketches

OpenAI has released its latest artificial intelligence model, which it said is capable of "thinking with images," meaning it can understand and analyze a user's sketches and diagrams, even if they're ...
GitHub

How to Use the TFT Model for Binary Classification on Time Series Data

I would like to know about how to configure the Temporal Fusion Transformer (TFT) model for training on a binary classification task over time series data. It's important to note that in my dataset, ...
IEEE

Black-Box Wiener-Hammerstein Model With Polytopic Dynamic Structure for Highly Non-Linear DC-DC Power Electronic Converters

Abstract: Due to the increasing presence of DC-DC power electronic converters in power distribution systems, having accurate models is essential for the analysis and design process. Black-box modeling ...
IEEE

Hybrid Deep-ANFN Model for Dimensionality Reduction and Classification

Abstract: This paper proposes a novel method to enhance classification performance and the reduction of high-dimensional feature maps by fusing deep learning with adaptive neuro-fuzzy network (ANFN).