Results 91 to 100 of about 3,227,937 (329)

User privacy prevention model using supervised federated learning‐based block chain approach for internet of Medical Things

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract This research focuses on addressing the privacy issues in healthcare advancement monitoring with the rapid establishment of the decentralised communication system in the Internet of Medical Things (IoMT). An integrated blockchain homomorphic encryption standard with an in‐build supervised learning‐based smart contract is designed to improvise ...
Chandramohan Dhasarathan, Mohammad Kamrul Hasan, Shayla Islam, Salwani Abdullah, Shailesh Khapre, Dalbir Singh, Abdulaziz A. Alsulami, Ali Alqahtani   +7 more
wiley   +1 more source

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

International Journal of Reconfigurable Computing, 2018
CPU has insufficient resources to satisfy the efficient computation of the convolution neural network (CNN), especially for embedded applications. Therefore, heterogeneous computing platforms are widely used to accelerate CNN tasks, such as GPU, FPGA ...
Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang   +9 more
doaj   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

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

Asynchronous Processing for Latent Fingerprint Identification on Heterogeneous CPU-GPU Systems

IEEE Access, 2020
Latent fingerprint identification is one of the most essential identification procedures in criminal investigations. Addressing this task is challenging as (i) it requires analyzing massive databases in reasonable periods and (ii) it is commonly solved ...
Andres J. Sanchez-Fernandez, Luis F. Romero, Daniel Peralta, Miguel Angel Medina-Perez, Yvan Saeys, Francisco Herrera, Siham Tabik   +6 more
doaj   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

An integration of autonomic computing with multicore systems for performance optimization in Industrial Internet of Things

IET Communications, EarlyView., 2022
Abstract The goal of this work is to investigate how the self‐awareness characteristic of autonomic computing, paired with existing performance optimization rules, may be used in applications to minimise multi‐core processor performance concerns. The suggested self‐awareness technique can assist applications in self‐execution while also assisting other
Surendra Kumar Shukla, Bhaskar Pant, Wattana Viriyasitavat, Devvret Verma, Sandeep Kautish, Gaurav Dhiman, Amandeep Kaur, Kannan Srihari, Sachi Nandan Mohanty   +8 more
wiley   +1 more source

Scalable deep text comprehension for Cancer surveillance on high-performance computing

BMC Bioinformatics, 2018
Background Deep Learning (DL) has advanced the state-of-the-art capabilities in bioinformatics applications which has resulted in trends of increasingly sophisticated and computationally demanding models trained by larger and larger data sets.
John X. Qiu, Hong-Jun Yoon, Kshitij Srivastava, Thomas P. Watson, J. Blair Christian, Arvind Ramanathan, Xiao C. Wu, Paul A. Fearn, Georgia D. Tourassi   +8 more
doaj   +1 more source

Gaussian Mixture Model‐Based Data Association Incorporating a Deep Learning Network for Multivehicle Tracking and Detection in Autonomous Driving Systems

Advanced Intelligent Systems, EarlyView.
This study introduces a real‐time light detection and ranging‐camera fusion framework for vehicle detection and tracking. Using a Gaussian mixture model‐based association and improved affinity metrics, the method enhances tracking reliability in dynamic conditions.
Muhammad Adeel Altaf, Min Young Kim
wiley   +1 more source

An ant colony genetic fusion routing algorithm based on soft define network

IET Networks, EarlyView., 2022
Abstract Aiming at the problem that there are many paths in data forwarding in soft define network (SDN) network, and the optimal path is difficult to find, combined with the advantages of ant colony algorithm and Genetic algorithm (GA), a routing control strategy based on the ant colony genetic fusion algorithm is proposed.
Kaixin Zhao, Yong Wei, Yang Zhang
wiley   +1 more source