Artificial Intelligence for Surface‐Enhanced Raman Spectroscopy
Surface‐enhanced Raman spectroscopy (SERS), well acknowledged as a fingerprinting
and sensitive analytical technique, has exerted high applicational value in a broad range of …
and sensitive analytical technique, has exerted high applicational value in a broad range of …
Machine learning for autonomous vehicle's trajectory prediction: A comprehensive survey, challenges, and future research directions
V Bharilya, N Kumar - Vehicular Communications, 2024 - Elsevier
The significant contribution of human errors, accounting for approximately 94%(with a
margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …
margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …
Generative adversarial networks review in earthquake-related engineering fields
Within seismology, geology, civil and structural engineering, deep learning (DL), especially
via generative adversarial networks (GANs), represents an innovative, engaging, and …
via generative adversarial networks (GANs), represents an innovative, engaging, and …
Enhancing multimodal cooperation via sample-level modality valuation
Y Wei, R Feng, Z Wang, D Hu - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
One primary topic of multimodal learning is to jointly incorporate heterogeneous information
from different modalities. However most models often suffer from unsatisfactory multimodal …
from different modalities. However most models often suffer from unsatisfactory multimodal …
ChatGPT-based scenario engineer: A new framework on scenario generation for trajectory prediction
The latest developments in parallel driving foreshadow the possibility of delivering
intelligence across organizations using foundation models. As is well-known, there are …
intelligence across organizations using foundation models. As is well-known, there are …
[HTML][HTML] AutoML: A systematic review on automated machine learning with neural architecture search
Abstract AutoML (Automated Machine Learning) is an emerging field that aims to automate
the process of building machine learning models. AutoML emerged to increase productivity …
the process of building machine learning models. AutoML emerged to increase productivity …
Enhancing coal-gangue object detection using GAN-based data augmentation strategy with dual attention mechanism
Coal separation based on computer vision has attracted substantial attention in recent
years. However, developing reliable object detection models relies on large-scale annotated …
years. However, developing reliable object detection models relies on large-scale annotated …
Transfer-learning and texture features for recognition of the conditions of construction materials with small data sets
Construction materials undergo appearance and textural changes during the construction
process. Accurate recognition of these changes is critical for effectively understanding the …
process. Accurate recognition of these changes is critical for effectively understanding the …
Opportunities and challenges of generative ai in construction industry: Focusing on adoption of text-based models
In the last decade, despite rapid advancements in artificial intelligence (AI) transforming
many industry practices, construction largely lags in adoption. Recently, the emergence and …
many industry practices, construction largely lags in adoption. Recently, the emergence and …
Bagm: A backdoor attack for manipulating text-to-image generative models
The rise in popularity of text-to-image generative artificial intelligence (AI) has attracted
widespread public interest. We demonstrate that this technology can be attacked to generate …
widespread public interest. We demonstrate that this technology can be attacked to generate …