Results 81 to 90 of about 307,816 (329)

Hyperspectral Anomaly Detection Based on Intrinsic Image Decomposition and Background Subtraction

IEEE Access
Hyperspectral anomaly detection is a detection of abnormal targets in a region based on spectral and spatial information under the premise of no prior knowledge of the target, which is a very important research topic in the field of remote sensing.
Jiao Jiao, Longlong Xiao, Chonglei Wang
doaj   +1 more source

High‐Entropy Magnetism of Murunskite

Advanced Functional Materials, EarlyView.
The study of murunskite (K2FeCu3S4) reveals that its magnetic and orbital order emerges in a simple I4/mmm crystal structure with complete disorder in the transition metal positions. Mixed‐valence Fe ions randomly occupy 1/4 of the tetrahedral sites, with the remaining 3/4 being filled by non‐magnetic Cu+ ions.
Davor Tolj, Priyanka Reddy, Ivica Živković, Luka Akšamović, Jian Rui Soh, Kamila Komȩdera, Izabela Biało, Naveen Kumar Chogondahalli Muniraju, Trpimir Ivšić, Mario Novak, Oksana Zaharko, Clemens Ritter, Thomas LaGrange, Wojciech Tabiś, Ivo Batistić, László Forró, Henrik M. Rønnow, Denis K. Sunko, Neven Barišić   +18 more
wiley   +1 more source

Single Pair of Weyl Points Evolve From Spin Group‐Protected Nodal Line in Half‐Metallic Ferromagnet V3S4

Advanced Functional Materials, EarlyView.
A spin group (SG)‐based mechanism is proposed to realize a single pair of Weyl points. PT‐symmetric nodal lines (NLs) persist under T‐breaking, protected by the combination of SG and P symmetry. When considering spin‐orbit coupling, the SG‐protected NL will split into Weyl points, which will also induce anomalous transport phenomena arising from ...
Shifeng Qian, Yao Zhang, Xiaowei Sheng, Xiuxian Yang, Gang Zhang, Junfeng Gao, Xiaotian Wang   +6 more
wiley   +1 more source

JointNet: Multitask Learning Framework for Denoising and Detecting Anomalies in Hyperspectral Remote Sensing

Remote Sensing
One of the significant challenges with traditional single-task learning-based anomaly detection using noisy hyperspectral images (HSIs) is the loss of anomaly targets during denoising, especially when the noise and anomaly targets are similar. This issue
Yingzhao Shao, Shuhan Li, Pengfei Yang, Fei Cheng, Yueli Ding, Jianguo Sun   +5 more
doaj   +1 more source

Atomic Size Misfit for Electrocatalytic Small Molecule Activation

Advanced Functional Materials, EarlyView.
This review explores the application and mechanisms of atomic size misfit in catalysis for small molecule activation, focusing on how structural defects and electronic properties can effectively lower the energy barriers of chemical bonds in molecules like H2O, CO2, and N2.
Ping Hong, Changfan Xu, Huaping Zhao, Yong Lei   +3 more
wiley   +1 more source

Collaborative Anomaly Detection

, 2022
In recommendation systems, items are likely to be exposed to various users and we would like to learn about the familiarity of a new user with an existing item. This can be formulated as an anomaly detection (AD) problem distinguishing between "common users" (nominal) and "fresh users" (anomalous). Considering the sheer volume of items and the sparsity
Bai, Ke, Zhang, Aonan, Li, Zhizhong, Heano, Ricardo, Wang, Chong, Carin, Lawrence   +5 more
openaire   +2 more sources

Single‐Step Conversion of Metal Impurities in CNTs to Electroactive Metallic Nitride Nanoclusters for Electrochemical CO2 Reduction

Advanced Functional Materials, EarlyView.
A single‐step, low‐temperature co‐pyrolysis process removes encapsulated seed metal NPs (10–50 nm) from CNTs, redistributing them as surface‐anchored metal and metal–nitride NCs (1–1.5 nm). Herein, Ni3N NCs achieve an ultra‐low onset overpotential for CO2 reduction to CO with >98% Faradaic efficiency across 100–700 mA cm−2.
Ahmed Badreldin, John Pellessier, Francisco Alejandro Ospina Acevedo, Siyuan Fang, Carter Racine, Jin Feng, Alvin Chang, Yulu Ge, Yang Gang, Shengyao Wang, Xiaokun Yang, Sergei Ivanov, Zhenxing Feng, Yun Hang Hu, Perla B. Balbuena, Ying Li   +15 more
wiley   +1 more source

Enhancing Time Series Anomaly Detection: A Knowledge Distillation Approach with Image Transformation

Sensors
Anomaly detection is critical in safety-sensitive fields, but faces challenges from scarce abnormal data and costly expert labeling. Time series anomaly detection is relatively challenging due to its reliance on sequential data, which imposes high ...
Haiwoong Park, Hyeryung Jang
doaj   +1 more source

Toward Supervised Anomaly Detection

Journal of Artificial Intelligence Research, 2013
Anomaly detection is being regarded as an unsupervised learning task as anomalies stem from adversarial or unlikely events with unknown distributions. However, the predictive performance of purely unsupervised anomaly detection often fails to match the required detection rates in many tasks and there exists a need for labeled data to guide the model ...
Goernitz, Nico, Kloft, Marius, Rieck, Konrad, Brefeld, Ulf   +3 more
openaire   +7 more sources

2D Multifunctional Spin‐Orbit Coupled Dirac Nodal Line Materials

Advanced Functional Materials, EarlyView.
A total of 473 nonmagnetic and antiferromagnetic 2D spin‐orbit coupled Dirac nodal line materials are screened, spanning 5 layer groups and 12 magnetic space groups. Furthermore, it integrates their topological properties with electride, multiferroic, and magnetic characteristics, revealing unique systems with expanded functionalities and promising ...
Weizhen Meng, Ying Liu, Jialin Gong, Yalong Jiao, Xiaoming Zhang, Wenxian Li, Zhenxiang Cheng, Tie Yang   +7 more
wiley   +1 more source