Results 91 to 100 of about 93,522 (265)

Detection of Bacterial Leaf Spot Disease in Sesame (Sesamum indicum L.) Using a U-Net Autoencoder

Remote Sensing
Hyperspectral imaging (HSI) integrates spectroscopy and imaging, providing detailed spectral–spatial information, and the selection of task-relevant wavelengths can streamline data acquisition and processing for field deployment.
Minju Lee, Jeseok Lee, Amit Ghimire, Yegyeong Bae, Tae-An Kang, Youngnam Yoon, In-Jung Lee, Choon-Wook Park, Byungwon Kim, Yoonha Kim   +9 more
doaj   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Denoising Autoencoder and Contrast Enhancement for RGB and GS Images with Gaussian Noise

Mathematics
Robust image processing systems require input images that closely resemble real-world scenes. However, external factors, such as adverse environmental conditions or errors in data transmission, can alter the captured image, leading to information loss ...
Armando Adrián Miranda-González, Alberto Jorge Rosales-Silva, Dante Mújica-Vargas, Edwards Ernesto Sánchez-Ramírez, Juan Pablo Francisco Posadas-Durán, Dilan Uriostegui-Hernandez, Erick Velázquez-Lozada, Francisco Javier Gallegos-Funes   +7 more
doaj   +1 more source

Quantum circuit autoencoder

Physical Review A
13 pages, 7 ...
Jun Wu, Hao Fu, Mingzheng Zhu, Haiyue Zhang, Wei Xie, Xiang-Yang Li   +5 more
openaire   +2 more sources

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

Advanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender, Marco Corrias, Cesare Franchini   +2 more
wiley   +1 more source

An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets

Future Internet
The rapid expansion of Edge and Industrial Internet of Things (IIoT) systems has intensified the risk and complexity of cyberattacks. Detecting advanced intrusions in these heterogeneous and high-dimensional environments remains challenging.
Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh   +2 more
doaj   +1 more source

Poisson Variational Autoencoder

Advances in Neural Information Processing Systems 37
Published as a NeurIPS 2024 Spotlight paper (https://openreview.net/forum?id=ektPEcqGLb)
Vafaii, Hadi, Galor, Dekel, Yates, Jacob L.   +2 more
openaire   +3 more sources

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Probabilistic Principal Component Analysis and Channel Attention for End-to-End Image Compression Optimization

IEEE Access
In recent years, deep learning has shown significant progress for image compression compared to traditional image compression methods. Although conventional standard-based methods are still used, they are limited in handling repetitive patterns and ...
Andri Agustav Wirabudi, Sung-Chang Lim, Woong Lim, Jeongil Seo, Haechul Choi   +4 more
doaj   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source