Results 71 to 80 of about 15,271 (229)

Usability of a deep learning platform for detecting radiographic bone loss and furcation involvement

Journal of Periodontology, EarlyView.
Abstract Background Assessing radiographic bone condition is important for periodontal diagnosis. The accuracy of radiographic interpretation depends highly on a clinician's experience and knowledge. This study aimed to develop a deep learning‐based online platform that aids clinicians in diagnosing periodontitis based on periapical radiographs and to ...
Chun‐Teh Lee, Tanjida Kabir, Alaa Alsaffar, Jiman Nelson, Sally Sheng, Hsiu‐Wan Meng, Mohammad Qali, Muhammad F. Walji, Xiaoqian Jiang, Shayan Shams   +9 more
wiley   +1 more source

Facial Expression Recognition with Swin Transformer

, 2022
The task of recognizing human facial expressions plays a vital role in various human-related systems, including health care and medical fields. With the recent success of deep learning and the accessibility of a large amount of annotated data, facial expression recognition research has been mature enough to be utilized in real-world scenarios with ...
Kim, Jun-Hwa, Kim, Namho, Won, Chee Sun
openaire   +2 more sources

GraphReco: Probabilistic Structure Recognition for Chemical Molecules

ChemistryOpen, EarlyView.
Molecule structure images are unfriendly for machine understanding, blocking productivity improvements in chemical data mining, drug discovery, and many other fields. We present a rule‐based probabilistic Optical Chemical Structure Recognition model to explain and tackle the ambiguity challenges in graph assembly.
Haidong Wang, Yuncheng Yu, Jyh‐Charn Liu   +2 more
wiley   +1 more source

Advanced deepfake detection leveraging swin transformer technology [PDF]

The widespread use of deepfake technology in recent years has made it extremely difficult to differentiate between real and fake images, usually AI-generated images.
Edalatpanah, Seyed Ahmad, Gourisaria, Mahendra Kumar, Mishra, Soumya Ranjan, Mohapatra, Hitesh   +3 more
core   +2 more sources

A pipeline to compile expert‐verified datasets of digitised herbarium specimens for automated plant identification to accelerate taxonomy

PLANTS, PEOPLE, PLANET, EarlyView.
Understanding and protecting plant life is essential for tackling the twin challenges of biodiversity loss and climate change. To support this, we have developed a new digital approach that helps identify plant species more quickly and accurately.
Jed Arno, Jérémie Morel, Fitiavana Rasaminirina, Juliene de Fátima Maciel‐Silva, Daniel Cahen, Damon P. Little, Daniele Silvestro, Alexandre Antonelli, Olwen Grace, Li Zhang, Isabel Larridon   +10 more
wiley   +1 more source

Secure pulmonary diagnosis using transformer-based approach to x-ray classification with KL divergence optimization [PDF]

Lung disease classification plays a significant part in the early discovery and diagnosis of respiratory conditions. This paper proposes a novel approach for lung disease classification utilizing two advanced deep learning models, MedViT and Swin ...
Alam, Shadab, Anand, Vatsala, Khan, Irfanullah, Shuaib, Mohammed, Ullah, Mehran   +4 more
core   +1 more source

AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam, Basit Raza, Muhammad Faheem, Aadil Raza   +3 more
wiley   +1 more source

Dynamic Adaptive Label Assignment for Tiny Object Detection in Remote Sensing Images

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT With the development of unmanned aerial vehicle and satellite technology, the application of tiny object detection in remote sensing images is becoming increasingly widespread. Although significant progress has been made in the accuracy and speed of object detection in recent years, performance declines sharply when general object detectors ...
Shuohao Shi, Qiang Fang, Xin Xu
wiley   +1 more source

Unsupervised Low Light Image Enhancement Using SNR-Aware Swin Transformer

, 2023
Image captured under low-light conditions presents unpleasing artifacts, which debilitate the performance of feature extraction for many upstream visual tasks.
Gao, Yanzeng, Hou, Yueen, Huang, Zihan, Luo, Zhijian, Tang, Jiahui   +4 more
core  

Self-Supervised Learning with Swin Transformers

, 2021
We are witnessing a modeling shift from CNN to Transformers in computer vision. In this work, we present a self-supervised learning approach called MoBY, with Vision Transformers as its backbone architecture. The approach basically has no new inventions, which is combined from MoCo v2 and BYOL and tuned to achieve reasonably high accuracy on ImageNet ...
Xie, Zhenda, Lin, Yutong, Yao, Zhuliang, Zhang, Zheng, Dai, Qi, Cao, Yue, Hu, Han   +6 more
openaire   +2 more sources