Results 221 to 230 of about 4,805,610 (298)

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Respiratory signal prediction based on adaptive boosting and multi-layer perceptron neural network. [PDF]

Phys Med Biol, 2017
Sun WZ, Jiang MY, Ren L, Dang J, You T, Yin FF.   +5 more
europepmc   +1 more source

Detecting Plateau Zokor (Eospalax baileyi) Mounds in UAV Imagery of Alpine Meadows Using Deep Learning Algorithms

Remote Sensing in Ecology and Conservation, EarlyView.
We developed PZM‐YOLO to automatically detect plateau zokor mounds in UAV imagery of alpine meadows. The model achieved reliable detection of small and densely distributed mounds under complex backgrounds, outperforming the baseline YOLOv5s. This framework supports mound counting, mound position, rodent impact assessment, and grassland restoration ...
Yang Yang, Limin Hua, Lianguo Wang, Jiazhen Li, Rui Dong, Siwei Yang   +5 more
wiley   +1 more source

Deceleration Planning Algorithm Based on Classified Multi-Layer Perceptron Models for Smart Regenerative Braking of EV in Diverse Deceleration Conditions. [PDF]

Sensors (Basel), 2019
Sim G, Min K, Ahn S, Sunwoo M, Jo K.
europepmc   +1 more source

From Prediction to Prevention: An Explainable GeoAI Framework for Flood Susceptibility and Urban Exposure Assessment Using Machine and Deep Learning Models

Sustainable Development, EarlyView.
ABSTRACT Rapid urbanisation and intensifying rainfall have increased cities' vulnerability to flooding, posing major challenges to sustainable development. Although machine learning models have improved flood prediction accuracy, most remain limited by their black‐box nature and lack of actionable insights.
Abdulwaheed Tella, Izni Zahidi, Chow Ming Fai, Chukwuma Okolie, Quoc Bao Pham   +4 more
wiley   +1 more source

Estimation of effective connectivity using multi-layer perceptron artificial neural network. [PDF]

Cogn Neurodyn, 2018
Talebi N, Nasrabadi AM, Mohammad-Rezazadeh I.   +2 more
europepmc   +1 more source

FEWT: Frequency‐Enhanced Wavelet‐Based Transformer for Multimodal Wheeled Bimanual Manipulation

SmartBot, EarlyView.
An embodied mobile bimanual robot learns dexterous manipulation skills through imitation learning with multimodal perception. The integration of vision, proprioception, and tactile sensing establishes a comprehensive perception–action loop, enabling the robot to continuously understand, interact with, and adapt to complex physical environments.
Jiaxin Huang, Hanyu Liu, Yunsheng Ma, Jian Shen, Yilin Zheng, Jiayi Wen, Zhigong Song   +6 more
wiley   +1 more source

Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi‐scenario applications, and translational prospects

Smart Molecules, EarlyView.
AI is transforming TPD by improving the design, prediction, and optimization of degraders such as PROTACs, molecular glues, and LYTACs. This review summarizes key AI‐driven advances, highlights applications across drug discovery stages, and discusses remaining challenges and future directions for accelerating the development of therapies against ...
Shuanglin Qin, Rui Peng, Guangshuai Zhang, Si Yan, Jin Xiao, Zishu Liu, Ziyu Tan, Qingqing Xie, Shangjie Li, Wei Luo, Xiaohe Xiao   +10 more
wiley   +1 more source

Peptide Fingerprinting of Single Protein Molecules Using In‐Plane Nanopore Sensors Integrated to an Extended Immobilized Nanoscale Enzymatic Reactor (eINER)

Small Methods, EarlyView.
The protein Time‐of‐Flight (P‐ToF) chip can peptide fingerprint a single protein molecule by subjecting it to a solid phase endopeptidase cleavage reaction in‐line with a combination of resistive pulse sensing of the resulting single peptides and machine‐learning aided identification.
Suresh Shivanka, Randy F. Espinal Cabrera, Maximillian Chibuike, Pramodi Vithanage, Indu A. Chandrasoma, Pubudu Premarathne, Matthew Verber, Steven A. Soper   +7 more
wiley   +1 more source

A Multi‐Sequence Adversarial Fusion U‐Net for Brain Tumor Image Segmentation

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
In the field of brain tumor image segmentation, in order to avoid the impact of insufficient number of training samples, the method of fusing multi‐modal MRI information before segmentation is widely used. However, when fusing different modal features, existing methods only add fixed weights to the features of each modality, resulting in insufficient ...
Jie Wang, Jinglu Hu
wiley   +1 more source