Results 201 to 210 of about 217,546 (313)
Voltage‐Summation‐Based Compute‐in‐Memory Technology with Capacitive Synaptic Devices
Compute‐in‐memory (CIM) technologies leveraging capacitive coupling offer significant advantages in energy efficiency and IR‐drop elimination. This work introduces voltage‐summation‐based CIM technology, employing capacitive synaptic devices for matrix–vector multiplication.
Jung Nam Kim+8 more
wiley +1 more source
Squeeze and multi‐context attention for polyp segmentation
Abstract Artificial Intelligence‐based Computer Aided Diagnostics (AI‐CADx) have been proposed to help physicians in reducing misdetection of polyps in colonoscopy examination. The heterogeneity of a polyp's appearance makes detection challenging for physicians and AI‐CADx.
Debayan Bhattacharya+3 more
wiley +1 more source
Summary: With the rapid development of quantum computing, a variety of quantum convolutional neural networks (QCNNs) are proposed. However, only 1/2n2 features of an n-qubits input are transferred to the next layer in a quantum pooling layer, which ...
Qingshan Wu+5 more
doaj
DeepMethyGene: a deep-learning model to predict gene expression using DNA methylations. [PDF]
Yan Y+5 more
europepmc +1 more source
Power allocation policies for convolutional and turbo coded systems over fading channels [PDF]
A. Rangarajan+2 more
openalex +1 more source
A Robotic Prosthetic Hand for Computer Mouse Operations
A soft prosthetic hand for computer mouse operations is introduced to assist users in completing diverse cursor control tasks. The designs of the hardware and software components are presented separately, followed by a user study conducted to assess the feasibility and acceptance of this system.
Ziming Chen+6 more
wiley +1 more source
Quantum block and convolutional codes from self-orthogonal product codes [PDF]
Markus Grassl, Martin Rötteler
openalex +1 more source
Machine learning of endoscopy images to identify, classify, and segment sinonasal masses
ABSTRACT Background We developed and assessed the performance of a machine learning model (MLM) to identify, classify, and segment sinonasal masses based on endoscopic appearance. Methods A convolutional neural network‐based model was constructed from nasal endoscopy images from patients evaluated at an otolaryngology center between 2013 and 2024 ...
Lirit Levi+10 more
wiley +1 more source
Explainable machine learning in cybersecurity: A survey
Abstract Machine learning (ML) techniques are increasingly important in cybersecurity, as they can quickly analyse and identify different types of threats from millions of events. In spite of the increasing number of possible applications of ML, successful adoption of ML models in cybersecurity still highly relies on the explainability of those models ...
Feixue Yan+4 more
wiley +1 more source
Gauge equivariant convolutional neural networks for diffusion MRI. [PDF]
Hussain U, Khan AR.
europepmc +1 more source