Results 141 to 150 of about 75,080 (277)

Simulation von Waldbewirtschaftung mittels Deep Neural Networks (DNNs)

Anthropogene Einflüsse haben bereits zu einer globalen Erwärmung von 1°C gegenüber vorindustrieller Zeit geführt. Es gibt große Unsicherheiten, wie veränderte Klimabedingungen die zukünftige Rolle von Waldökosystemen beeinflussen werden. Modellierung ist ein vielseitiges Werkzeug und ermöglicht komplexe Abläufe in Ökosystemen zu verstehen.
openaire  

Review on enhancing clinical decision support system using machine learning

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood, Usman Naseem, Junaid Rashid, Jungeun Kim, Imran Razzak   +4 more
wiley   +1 more source

Robust steganographic framework for securing sensitive healthcare data of telemedicine using convolutional neural network

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Data is the key element that runs the modern society. Large amounts of data are being released day by day as a result of many activities. The digital data is transferred through the Internet which may be vulnerable to attacks while transmitting. Especially, the medical data is observed to be of at most importance.
Rupa Ch, Venkayya Yadlapalli, Suhana Sulthana Sk, G. Thippa Reddy, Sandeep Kautish   +4 more
wiley   +1 more source

AI‐enabled bumpless transfer control strategy for legged robot with hybrid energy storage system

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Designing Hybrid energy storage system (HESS) for a legged robot is significant to improve the motion performance and energy efficiency of the robot. However, switching between the driving mode and regenerative braking mode in the HESS may generate a torque bump, which has brought significant challenges to the stability of the robot locomotion.
Zhiwu Huang, Zi Yu, Hui Peng, Zixuan Wang, Xiaokang Dai, Weirong Liu, Jing Wang   +6 more
wiley   +1 more source

Brain‐RetinaNet: Detection of Brain Tumour Using an Improved RetinaNet in Magnetic Resonance Imaging

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Brain tumours disrupt the normal functioning of the brain and, if left untreated, can invade surrounding tissues, blood vessels, and nerves, posing a severe threat. Consequently, early detection is crucial to prevent tragic outcomes. Distinguishing brain tumours through manual detection poses a significant challenge given their diverse ...
Rashid Iqbal, Rabbia Mahum, Mohamed Sharaf, Javed Ali Khan   +3 more
wiley   +1 more source

Deep neural network-based biostatistical analysis for disease marker screening. [PDF]

Sci Rep
Wang X.
europepmc   +1 more source

Robotic Cell Micromanipulation Skill Learning via Imitation‐Enhanced Reinforcement Learning

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Humans can learn complex and dexterous manipulation tasks by observing videos, imitating and exploring. Multiple end‐effectors manipulation of free micron‐sized deformable cells is one of the challenging tasks in robotic micromanipulation. We propose an imitation‐enhanced reinforcement learning method inspired by the human learning process ...
Youchao Zhang, Fanghao Wang, Xiangyu Guo, Yibin Ying, Mingchuan Zhou, Zhongliang Jiang, Alois Knoll   +6 more
wiley   +1 more source

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

Unpacking Genomic Biomarkers for Programmed Cell Death Receptor-1 Immunotherapy Success in Non-Small Cell Lung Cancer Using Deep Neural Networks: Quantitative Study. [PDF]

JMIR Bioinform Biotechnol
Mubarak R, Anik FI, Rodriguez JT, Sakib N, Rahman MA.   +4 more
europepmc   +1 more source

Deep learning model for enhanced power loss prediction in the frequency domain for magnetic materials

IET Power Electronics, EarlyView.
This paper outlines the methodology for predicting power loss in magnetic materials. A neural network based method is introduced, which adopts a long short‐term memory network, expressing the core loss as a function of magnetic flux density in the frequency domain, temperature, frequency, and classification of the waveforms.
Dixant Bikal Sapkota, Puskar Neupane, Mecon Joshi, Shahabuddin Khan   +3 more
wiley   +1 more source