Results 51 to 60 of about 64,275 (248)

Autoencoding Topographic Factors [PDF]

Journal of Computational Biology, 2019
Topographic factor models separate overlapping signals into latent spatial functions to identify correlation structure across observations. These methods require the underlying structure to be held fixed and are not robust to deviations commonly found across images.
Antonio, Moretti, Andrew, Stirn, Gabriel, Marks, Itsik, Pe'er   +3 more
openaire   +2 more sources

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

Anomaly detection of smart grid stealing network attacks based on deep autoencoder

Dianzi Jishu Yingyong
Existing anomaly detectors in AMIs suffer from shallow architectures, which impede their ability to capture temporal correlations and complex patterns in electricity consumption data, thus impact detection performance adversely.
Huang Yan, Li Jincan, Yang Xiaqin, Li Pei, Li Zi   +4 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

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

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

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Scalable and Efficient Protein Secondary Structure Prediction Using Autoencoder-Reduced ProtBERT Embeddings

Applied Sciences
This study proposes a deep learning framework for Protein Secondary Structure Prediction (PSSP) that prioritizes computational efficiency while preserving classification accuracy.
Yahya Najib Hamood Al-Shameri, İrfan Kösesoy, Hakan Gündüz, Ömer Faruk Yılmaz   +3 more
doaj   +1 more source

De Novo Multi‐Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning

Advanced Science, EarlyView.
Current AI‐driven peptide discovery often overlooks complex structural data. This study presents M3‐CAD, a generative pipeline that leverages 3D voxel coloring and a massive database of over 12 000 peptides to capture nuanced physicochemical contexts.
Xiaojuan Li, Haifan Gong, Yue Wang, Yinuo Zhao, Lixiang Li, Peijing Bao, Qingzhou Kong, Jialu Fu, Boyao Wan, Yumeng Zhang, Jinghui Zhang, Jiekun Ni, Zhongxue Han, Xueping Nan, Kunping Ju, Longfei Sun, Yuerui Ma, Huijun Chang, Mengqi Zheng, Yanbo Yu, Xiaoyun Yang, Xiuli Zuo, Haina Wang, Yanqing Li   +23 more
wiley   +1 more source