Results 151 to 160 of about 118,476 (365)

SONAR Images Denoising

, 2011
International ...
Isar, Alexandru, Adam, Ioana, Nafornita, Corina, Moga, Sorin   +3 more
openaire   +4 more sources

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Single‐Particle Mid‐Infrared Photothermal Imaging Reveals Hidden Heterogeneity in Real‐World Micro‐ and Nanoplastics

Advanced Science, EarlyView.
Mid‐infrared photothermal imaging enables multidimensional profiling of micro‐ and nanoplastics in bottled water. A total of 9.9 × 104 particles L−1 is detected, with 64% in the nanoscale regime. Spectral evolution, including peak narrowing and band shifts, reveals local chain reorganization in polyethylene terephthalate (PET), highlighting intrinsic ...
Xinyu Deng, Yongqing Zhang, Xiaobin Tang, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Motion Capture in Mixed-Reality Applications: A Deep Denoising Approach

Virtual Worlds
Motion capture is a fundamental technique in the development of video games and in film production to animate a virtual character based on the movements of an actor, creating more realistic animations in a short amount of time.
André Correia Gonçalves, Rui Jesus, Pedro Mendes Jorge   +2 more
doaj   +1 more source

Deterministic Discrete Denoising

CoRR
We propose a deterministic denoising algorithm for discrete-state diffusion models. The key idea is to derandomize the generative reverse Markov chain by introducing a variant of the herding algorithm, which induces deterministic state transitions driven by weakly chaotic dynamics. It serves as a direct replacement for the stochastic denoising process,
Suzuki, Hideyuki, Kurebayashi, Wataru, Yamashita, Hiroshi   +2 more
openaire   +2 more sources

Schooling Trajectories and the Development of Brain Dynamics: A Comparative Study of Montessori and Traditional Education

Advanced Science, EarlyView.
We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua, Anira Escrichs, Yonatan Sanz Perl, Morten L. Kringelbach, Adele Diamond, Solange Denervaud, Gustavo Deco   +6 more
wiley   +1 more source

Can Denoising Enhance Prediction Accuracy of Learning Models? A Case of Wavelet Decomposition Approach

Forecasting
Denoising is an integral part of the data pre-processing pipeline that often works in conjunction with model development for enhancing the quality of data, improving model accuracy, preventing overfitting, and contributing to the overall robustness of ...
C. Tamilselvi, Md Yeasin, Ranjit Kumar Paul, Amrit Kumar Paul   +3 more
doaj   +1 more source

Planelets: A New Analysis Tool For Planar Feature Extraction [PDF]

, 2004
Locally planar structures, formed by sweeping edges of objects, are commonly found in video sequences and convey most of the useful information. In this paper, the issue of efficient representation of such structures is addressed.
Yao, Zhen, Nasir Rajpoot Roland, Roland Wilson, Wilson, Roland, Zhen Yao, Rajpoot, Nasir M.   +5 more
core  

Continuous online monitoring of partial discharges in high voltage cables

, 2004
This paper reviews data acquisition, transmission and processing methodologies for continuous online monitoring of partial discharges in power cable systems.
Tian, Y., Sutton, S.J., Lewin, P.L., Swingler, S.G., Wilkinson, J.S.   +4 more
core   +1 more source

MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion

Advanced Science, EarlyView.
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong, Ji Ma, Yidan Lu, Jiahui Zhang, Wanyue Li, Yeke Chen, Teng Zhang, Xuechao Chen, Zhangguo Yu, Peng Lu   +9 more
wiley   +1 more source