Adaptive ensembles of fine-tuned transformers for llm-generated text detection

Z Lai, X Zhang, S Chen - arXiv preprint arXiv:2403.13335, 2024 - arxiv.org
Large language models (LLMs) have reached human-like proficiency in generating diverse
textual content, underscoring the necessity for effective fake text detection to avoid potential …

Development and application of a monte carlo tree search algorithm for simulating da vinci code game strategies

Y Zhang, M Zhu, K Gui, J Yu, Y Hao, H Sun - arXiv preprint arXiv …, 2024 - arxiv.org
In this study, we explore the efficiency of the Monte Carlo Tree Search (MCTS), a prominent
decision-making algorithm renowned for its effectiveness in complex decision environments …

Research on intelligent aided diagnosis system of medical image based on computer deep learning

J Yuan, L Wu, Y Gong, Z Yu, Z Liu, S He - arXiv preprint arXiv:2404.18419, 2024 - arxiv.org
This paper combines Struts and Hibernate two architectures together, using DAO (Data
Access Object) to store and access data. Then a set of dual-mode humidity medical image …

Research on the application of deep learning in medical image segmentation and 3d reconstruction

Y Zi, Q Wang, Z Gao, X Cheng, T Mei - Academic Journal of Science …, 2024 - drpress.org
Medical image segmentation (MIS) and 3D reconstruction are crucial research directions in
the field of medical imaging, which is of great significance for disease diagnosis, treatment …

Leveraging deep learning and xception architecture for high-accuracy mri classification in alzheimer diagnosis

S Li, H Qu, X Dong, B Dang, H Zang, Y Gong - arXiv preprint arXiv …, 2024 - arxiv.org
Exploring the application of deep learning technologies in the field of medical diagnostics,
Magnetic Resonance Imaging (MRI) provides a unique perspective for observing and …

Research on Disease Prediction Model Construction Based on Computer AI deep Learning Technology

Y Lin, M Li, Z Zhu, Y Feng, L Xiao… - 2024 IEEE 2nd …, 2024 - ieeexplore.ieee.org
The prediction of disease risk factors can screen vulnerable groups for effective prevention
and treatment, so as to reduce their morbidity and mortality. Machine learning has a great …

Deep representation learning for multi-functional degradation modeling of community-dwelling aging population

S Chen, X Liu, Y Li, J Wu, H Yao - arXiv preprint arXiv:2404.05613, 2024 - arxiv.org
As the aging population grows, particularly for the baby boomer generation, the United
States is witnessing a significant increase in the elderly population experiencing …

TokenUnify: Scalable Autoregressive Visual Pre-training with Mixture Token Prediction

Y Chen, H Shi, X Liu, T Shi, R Zhang, D Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
Autoregressive next-token prediction is a standard pretraining method for large-scale
language models, but its application to vision tasks is hindered by the non-sequential nature …

Optimization and performance evaluation of deep learning algorithm in medical image processing

J Zhang, L Xiao, Y Zhang, J Lai, Y Yang - Frontiers in Computing and …, 2024 - drpress.org
In this paper, the optimization and performance evaluation of deep learning algorithm in
medical image processing are studied. Firstly, the paper introduces the importance and …

Research and Application of Deep Learning in Medical Image Reconstruction and Enhancement

Y Gong, H Qiu, X Liu, Y Yang, M Zhu - Frontiers in Computing and …, 2024 - drpress.org
In recent years, deep learning technology has made remarkable progress in medical image
reconstruction and enhancement, and has become one of the research hotspots in the field …