Results 51 to 60 of about 14,221 (268)

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Interpretability-Aware Industrial Anomaly Detection Using Autoencoders

IEEE Access, 2023
The past decade has witnessed wide applications of deep neural networks in anomaly detection. However, the dearth of interpretability in neural networks often hinders their reliability, especially for industrial applications where practical users heavily
Rui Jiang, Yijia Xue, Dongmian Zou
doaj   +1 more source

AutoEncoder by Forest

Proceedings of the AAAI Conference on Artificial Intelligence, 2018
Auto-encoding is an important task which is typically realized by deep neural networks (DNNs) such as convolutional neural networks (CNN). In this paper, we propose EncoderForest (abbrv. eForest), the first tree ensemble based auto-encoder.
Ji Feng, Zhi-Hua Zhou
openaire   +2 more sources

Evidence for Itinerant Ferromagnetic Flat Bands Producing Large Transverse Responses

Advanced Materials, EarlyView.
Itinerant ferromagnetic flat bands are demonstrated in GdCo5 with a high Curie temperature of 940K, a stacked honeycomb–kagome lattice, through angle‐resolved photoemission spectroscopy and magneto‐thermoelectric measurements. These topological flat bands generate large Berry curvaturte, producing gigantic anomalous Nernst effect with record‐high ...
Susumu Minami, Yangming Wang, Seigo Souma, Hiroto Nakamura, Akito Sakai, Takumi Osumi, Hang Su, Hikaru Watanabe, Shun'ichiro Kurosawa, Rikuto Oiwa, Daisuke Nishio‐Hamane, Kosuke Nakayama, Takuya Nomoto, Ryotaro Arita, Takafumi Sato, Satoru Nakatsuji   +15 more
wiley   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Enhancing anomaly detection with topology-aware autoencoders

Machine Learning: Science and Technology
Anomaly detection in high-energy physics is essential for identifying new physics beyond the Standard Model. Autoencoders provide a signal-agnostic approach but are limited by the topology of their latent space.
Vishal S Ngairangbam, Błażej Rozwoda, Kazuki Sakurai, Michael Spannowsky   +3 more
doaj   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection

IEEE Access
Surveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods.
Asim Niaz, Sareer Ul Amin, Shafiullah Soomro, Hamza Zia, Kwang Nam Choi   +4 more
doaj   +1 more source

DEEP NON-NEGATIVE MATRIX FACTORIZATION MODEL FOR CLUSTERING-BASED IMAGE DENOISING [PDF]

Proceedings on Engineering Sciences
Technologies like self-driving cars and cleaning robots are emerging as mainstream technologies. These technologies make use of cognitive recognition.
Shaily Malik , Nishtha Jatana , Divya Jatain , Geetanjali Sharma , Vaani Garg, Amita Yadav   +5 more
doaj   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

Advanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu, Mengyao Xiao, Zhouli Sui, Yinpeng Wang, Daoye Zheng, Yuxin Liu, Luwei Wang, Huajun Liu, Chengkuo Lee   +8 more
wiley   +1 more source