Results 91 to 100 of about 276,034 (269)

Spectral Representation of Neurochemicals With Phase, Frequency Offset, and Lineshape Invariance: Application to JPRESS for In Vivo Concentration and T2 Mapping by Deep Learning

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Using artificial intelligence neural networks to generate a representation that maps the input directly to neurochemical concentrations and metabolite‐level average transverse relaxation times (T2). Methods The proposed model used time‐domain JPRESS data as input and was trained to be invariant to phase shifts, frequency offsets, and ...
Yan Zhang, Jun Shen
wiley   +1 more source

An Interpretable TCN– Transformer Framework for Lithium‐Ion Battery State of Health Estimation Using SHAP Analysis

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Accurate state of health (SOH) estimation of Li‐ion batteries is essential for ensuring safety, reliability, and prolonging battery lifespan in energy storage systems and electric vehicles. This study proposes a hybrid temporal convolutional network (TCN)–transformer framework that effectively captures both short‐term temporal dynamics and ...
Fusen Guo, Zhibo Zhang, Xuzhe Ma, Lin Li, Hailing Zhou, Chaojie Li, Huadong Mo   +6 more
wiley   +1 more source

Terrain Classification for Planetary Rovers Using Wireless In‐Wheel Sensor Modules and Machine Learning

Journal of Field Robotics, EarlyView.
ABSTRACT Safe and reliable mobility over different kinds of ground is important for planetary rovers on space missions. Since terrain changes might affect the mobility of the rover, energy consumption, and safety, detecting the type of ground in real‐time is vital.
Md Masrul Khan, Sultan Shaharea, Manseeb M. Mannaf, Shihab Ahemed, Fahim Islam Anik, Md Jarir Hossain, Helal An Nahiyan, Sourav Karmaker   +7 more
wiley   +1 more source

Opportunities for 2D‐Material‐Based Multifunctional Devices and Systems in Bioinspired Neural Networks

Small, EarlyView.
Bio‐inspired computing offers a route to highly energy‐efficient artificial intelligence. The unique physical properties of two‐dimensional (2D) materials can further enhance such computing approaches. This perspective highlights recent developments in 2D materials‐based neuromorphic devices and discusses future opportunities for integrating such novel
Jin Feng Leong, Maheswari Sivan, Jieming Pan, Zihang Fang, Jianan Li, Zefeng Xu, Shi Zhao, Quanzhen Wan, Evgeny Zamburg, Aaron Voon‐Yew Thean   +9 more
wiley   +1 more source

EPCMSDB: Design of an ensemble predictive control model for solar PV MPPT deployments via dual bioinspired optimizations

Science and Technology for Energy Transition
With the increasing demand for renewable energy, solar power has emerged as a promising option for sustainable power generation. However, the effectiveness and efficiency of solar power systems rely on the ability to effectively manage their performance,
Hole Shreyas Rajendra, Das Goswami Agam
doaj   +1 more source

Spatio-Temporal Deep Learning Models for Tip Force Estimation During Needle Insertion

, 2019
Purpose. Precise placement of needles is a challenge in a number of clinical applications such as brachytherapy or biopsy. Forces acting at the needle cause tissue deformation and needle deflection which in turn may lead to misplacement or injury. Hence,
Antoni, Sven-Thomas, Gessert, Nils, Hamann, Moritz Franz, Jünemann, Klaus-Peter, Meyer, David, Otte, Christoph, Priegnitz, Torben, Saathoff, Thore, Schlaefer, Alexander   +8 more
core  

Advanced Hybrid Techniques for Cyberattack Detection and Defense in IoT Networks

SECURITY AND PRIVACY, Volume 8, Issue 2, March/April 2025.
ABSTRACT The Internet of Things (IoT) represents a vast network of devices connected to the Internet, making it easier for users to connect to modern technology. However, the complexity of these networks and the large volume of data pose significant challenges in protecting them from persistent cyberattacks, such as distributed denial‐of‐service (DDoS)
Zaed S. Mahdi, Rana M. Zaki, Laith Alzubaidi   +2 more
wiley   +1 more source

Application of deep learning techniques for analysis and prediction of particulate matter at Kota city, India

EQA
Air pollution significantly threatens human health and the environment, making accurate prediction of pollutant concentrations crucial for effective mitigation.
Lovish Sharma, Hajari Singh, Mahendra Pratap Choudhary   +2 more
doaj   +1 more source

Development of a Time Series E-Commerce Sales Prediction Method for Short-Shelf-Life Products Using GRU-LightGBM

Applied Sciences
Effective sales prediction for e-commerce would assist retailers in developing accurate production and inventory control plans, which would further help them to reduce inventory costs and overdue losses.
Yong Chen, Xian Xie, Zhi Pei, W. Yi, Cheng Wang, Wenzhu Zhang, Zuzhen Ji   +6 more
semanticscholar   +1 more source

MVI‐Depth: Multi‐View Indoor Depth Estimation Based on the Fusion of Semantic Information

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Compared to monocular depth estimation, multi‐view depth estimation often yields more accurate results. However, traditional multi‐view depth estimation methods often fail to leverage semantic information fully and struggle to effectively fuse information from multiple views, leading to suboptimal prediction performance in challenging ...
Ying Zhu, Buyun Chen, Hong Liu, Xia Li
wiley   +1 more source