Results 51 to 60 of about 8,876 (216)

BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models

Advanced Intelligent Systems, EarlyView.
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan, Kang Fu, Sijing Wu, Yunhao Li, Zicheng Zhang, Qiang Hu, Xiongkuo Min, Guangtao Zhai   +7 more
wiley   +1 more source

Zero Watermarking Using Convolutional Additive Self‐Attention Vision Transformer and Discrete Wavelet Transform‐Variance‐Based Feature Descriptor for Medical Image Security in Mobile Healthcare Services

Advanced Intelligent Systems, EarlyView.
A zero‐watermarking algorithm that combines a refined convolutional additive self‐attention vision transformer (CAS‐ViT) with a discrete wavelet transform variance‐based feature descriptor (DVFD) is proposed for protecting the privacy of medical images in mobile healthcare services.
Pei Liu, Yan Yan, Hao Huang, Ping Wang, Weirong Qin, Xiangjian Zuo, Yongqin Li   +6 more
wiley   +1 more source

Brain Tumor Detection using Swin Transformers

CoRR, 2023
The first MRI scan was done in the year 1978 by researchers at EML Laboratories. As per an estimate, approximately 251,329 people died due to primary cancerous brain and CNS (Central Nervous System) Tumors in the year 2020. It has been recommended by various medical professionals that brain tumor detection at an early stage would help in saving many ...
Prateek A. Meshram, Suraj Joshi, Devarshi Mahajan   +2 more
openaire   +2 more sources

Fine-Grained Ship Classification by Combining CNN and Swin Transformer

, 2022
The mainstream algorithms used for ship classification and detection can be improved based on convolutional neural networks (CNNs). By analyzing the characteristics of ship images, we found that the difficulty in ship image classification lies in ...
Yalun Zhang, Qingxia Xu, Liang Huang, Fengxiang Wang   +3 more
core   +1 more source

VALIANT: A Vision‐Authenticity Language Framework Through Integrated Experts and Aligned Numerical‐Textual Descriptors for Citri Reticulatae Pericarpium

Advanced Intelligent Systems, EarlyView.
Visual features, numerical descriptors, and controlled textual attributes extracted from smartphone images of Chenpi are integrated by VALIANT, a tailored multimodal framework for simultaneous storage‐age classification and authenticity verification. The workflow distinguishes genuine products from suspicious standard operating procedure mimics while ...
Simon C. K. Chan, Bingxin Huang, Hannah H. Kim, Wentao Yu, Yinqian Luo, Terence T. W. Wong   +5 more
wiley   +1 more source

MV-Swin-T: Mammogram Classification with Multi-View Swin Transformer

2024 IEEE International Symposium on Biomedical Imaging (ISBI)
Traditional deep learning approaches for breast cancer classification has predominantly concentrated on single-view analysis. In clinical practice, however, radiologists concurrently examine all views within a mammography exam, leveraging the inherent correlations in these views to effectively detect tumors. Acknowledging the significance of multi-view
Sushmita Sarker, Prithul Sarker, George Bebis, Alireza Tavakkoli   +3 more
openaire   +3 more sources

Small Object Detection for Birds with Swin Transformer

2023 18th International Conference on Machine Vision and Applications (MVA), 2023
Object detection is the task of detecting objects in an image. In this task, the detection of small objects is particularly difficult. Other than the small size, it is also accompanied by difficulties due to blur, occlusion, and so on. Current small object detection methods are tailored to small and dense situations, such as pedestrians in a crowd or ...
Da Huo, Marc A. Kastner 0001, Tingwei Liu, Yasutomo Kawanishi, Takatsugu Hirayama, Takahiro Komamizu, Ichiro Ide   +6 more
openaire   +2 more sources

SwinOCSR: end-to-end optical chemical structure recognition using a Swin Transformer

Journal of Cheminformatics, 2022
Optical chemical structure recognition from scientific publications is essential for rediscovering a chemical structure. It is an extremely challenging problem, and current rule-based and deep-learning methods cannot achieve satisfactory recognition ...
Zhanpeng Xu, Jianhua Li, Zhaopeng Yang, Shiliang Li, Honglin Li   +4 more
doaj   +1 more source

Leveraging Big Multitemporal Multisource Satellite Data and Artificial Intelligence for the Detection of Complex and Invisible Features: The Case of Extensive Irrigation Mapping

Archaeological Prospection, EarlyView.
ABSTRACT The detection of buried or obscured archaeological features remains a central challenge in landscape archaeology, particularly in the irrigated floodplains of Mesopotamia where levees and canals formed the basis of complex agrarian systems. This study presents a deep learning–based approach for the large‐scale, automated detection of ancient ...
Nazarij Buławka, Hector A. Orengo, Felipe Lumbreras Ruiz, Iban Berganzo‐Besga, Ekta Gupta   +4 more
wiley   +1 more source

Fully automated three‐dimensional deep learning‐based magnetic resonance imaging segmentation of brain cavities in epilepsy surgery

Epilepsia, EarlyView.
Abstract Objective There are several clinical and research applications for determining the amount of brain tissue resected after epilepsy surgery; however, manual segmentation of postoperative magnetic resonance imaging (MRI) is imprecise and time‐consuming.
Raphael Fernandes Casseb, Brunno Machado de Campos, Wallace Souza Loos, Marcelo Eduardo Ramos Barbosa, Marina Koutsodontis Machado Alvim, Gabriel Chagas Lutfala Paulino, Enrico Ghizoni, Francesco Pucci, Samuel Worrell, Clarissa Lin Yassuda, Roberto Medeiros de Souza, Lara Jehi, Fernando Cendes   +12 more
wiley   +1 more source