Efficiency optimization of large-scale language models based on deep learning in natural language processing tasks
The internal structure and operation mechanism of large-scale language models are
analyzed theoretically, especially how Transformer and its derivative architectures can …
analyzed theoretically, especially how Transformer and its derivative architectures can …
Predicting stock market trends using lstm networks: overcoming RNN limitations for improved financial forecasting
In recent years, stocks have increasingly attracted our attention. The inherent volatility of
stock prices, often caused by national and social policies, makes it challenging for investors …
stock prices, often caused by national and social policies, makes it challenging for investors …
Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation
Recent advancements in artificial intelligence (AI) have precipitated a paradigm shift in
medical imaging, particularly revolutionizing the domain of brain imaging. This paper …
medical imaging, particularly revolutionizing the domain of brain imaging. This paper …
Automated identification of breast cancer type using novel multipath transfer learning and ensemble of classifier
SS Nair, M Subaji - IEEE Access, 2024 - ieeexplore.ieee.org
Breast cancer, a global health concern, demands innovative diagnostic approaches. The
potential of AI (Artificial Intelligence) and ML (Machine Learning) in breast cancer diagnosis …
potential of AI (Artificial Intelligence) and ML (Machine Learning) in breast cancer diagnosis …
The application of artificial intelligence technology in assembly techniques within the industrial sector
B Hong, P Zhao, J Liu, A Zhu, S Dai… - Journal of Artificial …, 2024 - ojs.boulibrary.com
Industry 4.0 aims to address the issues of low accuracy and efficiency in the identification
and positioning of components during machine tool processing and assembly. To this end, a …
and positioning of components during machine tool processing and assembly. To this end, a …
Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Study
This paper proposes a medical literature summary generation method based on the BERT
model to address the challenges brought by the current explosion of medical information. By …
model to address the challenges brought by the current explosion of medical information. By …
Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis
This study introduces the Hybrid Multi-modal VGG (HM-VGG) model, a cutting-edge deep
learning approach for the early diagnosis of glaucoma. The HM-VGG model utilizes an …
learning approach for the early diagnosis of glaucoma. The HM-VGG model utilizes an …
Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithm
This paper explores the application of knowledge distillation technology in target detection
tasks, especially the impact of different distillation temperatures on the performance of …
tasks, especially the impact of different distillation temperatures on the performance of …
Advancing Automated Surveillance: Real-Time Detection of Crown-of-Thorns Starfish via YOLOv5 Deep Learning
G Xu, Y Xie, Y Luo, Y Yin, Z Li… - Journal of Theory and …, 2024 - centuryscipub.com
Abstract The Great Barrier Reef faces significant threats from crown-of-thorns starfish
(COTS), which consume coral polyps and contribute to reef degradation. Traditional …
(COTS), which consume coral polyps and contribute to reef degradation. Traditional …
Efficient and Aesthetic UI Design with a Deep Learning-Based Interface Generation Tree Algorithm
S Duan, R Zhang, M Chen, Z Wang, S Wang - arXiv preprint arXiv …, 2024 - arxiv.org
This paper presents a novel method for user interface (UI) generation based on the
Transformer architecture, addressing the increasing demand for efficient and aesthetically …
Transformer architecture, addressing the increasing demand for efficient and aesthetically …