A comparative study of generative adversarial networks for image recognition algorithms based on deep learning and traditional methods
In this paper, an image recognition algorithm based on the combination of deep learning
and generative adversarial network (GAN) is studied, and compared with traditional image …
and generative adversarial network (GAN) is studied, and compared with traditional image …
Attention mechanism and context modeling system for text mining machine translation
This paper advances a novel architectural schema anchored upon the Transformer
paradigm and innovatively amalgamates the K-means categorization algorithm to augment …
paradigm and innovatively amalgamates the K-means categorization algorithm to augment …
Analyzing diversity in healthcare LLM research: A scientometric perspective
The deployment of large language models (LLMs) in healthcare has demonstrated
substantial potential for enhancing clinical decision-making, administrative efficiency, and …
substantial potential for enhancing clinical decision-making, administrative efficiency, and …
Advancing Emotional Analysis with Large Language Models
The objective of this research is to enhance the efficiency of intelligence acquisition through
sentiment analysis of public opinion, a crucial element of open-source intelligence, utilizing …
sentiment analysis of public opinion, a crucial element of open-source intelligence, utilizing …
Algorithm Research of ELMo Word Embedding and Deep Learning Multimodal Transformer in Image Description
Zero sample learning is an effective method for data deficiency. The existing embedded zero
sample learning methods only use the known classes to construct the embedded space, so …
sample learning methods only use the known classes to construct the embedded space, so …
Investigating financial risk behavior prediction using deep learning and big data
K Xu, Y Wu, Z Li, R Zhang… - International Journal of …, 2024 - ijirem.irpublications.org
This paper introduces a sophisticated deep learning model designed to predict high-risk
behaviors in financial traders by analyzing vast amounts of transaction data. The model …
behaviors in financial traders by analyzing vast amounts of transaction data. The model …
Advanced Financial Fraud Detection Using GNN-CL Model
Y Cheng, J Guo, S Long, Y Wu, M Sun… - arXiv preprint arXiv …, 2024 - arxiv.org
The innovative GNN-CL model proposed in this paper marks a breakthrough in the field of
financial fraud detection by synergistically combining the advantages of graph neural …
financial fraud detection by synergistically combining the advantages of graph neural …
Applying Conditional Generative Adversarial Networks for Imaging Diagnosis
This study introduces an innovative application of Conditional Generative Adversarial
Networks (C-GAN) integrated with Stacked Hourglass Networks (SHGN) aimed at …
Networks (C-GAN) integrated with Stacked Hourglass Networks (SHGN) aimed at …
The design of autonomous uav prototypes for inspecting tunnel construction environment
Y Dong - arXiv preprint arXiv:2408.07286, 2024 - arxiv.org
This article presents novel designs of autonomous UAV prototypes specifically developed
for inspecting GPS-denied tunnel construction environments with dynamic human and …
for inspecting GPS-denied tunnel construction environments with dynamic human and …
Exploiting Diffusion Prior for Out-of-Distribution Detection
Out-of-distribution (OOD) detection is crucial for deploying robust machine learning models,
especially in areas where security is critical. However, traditional OOD detection methods …
especially in areas where security is critical. However, traditional OOD detection methods …