Results 71 to 80 of about 14,679 (231)

Improving Benign and Malignant Classifications in Mammography with ROI-Stratified Deep Learning

Bioengineering
Deep learning has achieved widespread adoption for medical image diagnosis, with extensive research dedicated to mammographic image analysis for breast cancer screening.
Kenji Yoshitsugu, Kazumasa Kishimoto, Tadamasa Takemura   +2 more
doaj   +1 more source

Efficient Waste Classification in Cisadane River Using Vision Transformer and Swin Transformer Architectures [PDF]

The increasing volume of waste in rivers has become a serious environmental problem. This study proposes the implementation of Artificial Intelligence (AI)-based models, specifically Vision Transformer (ViT) and Swin Transformer, for an automatic waste ...
Mutiarawan, Rezza Anugrah, Surahmat, Asep   +1 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

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

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

Pixel Lens: A Granular Assessment of Saliency Explanations

Artificial Intelligence for Engineering, EarlyView.
We propose a pipeline that detects shortcut‐dominated classifiers by comparing predictions on clean and shortcut‐perturbed images and checking dominance via a Shapley‐based ground‐truth explainer. The workflow quantifies the explanation quality of different explainable artificial intelligence (XAI) methods.
Kanglong Fan, Chen Ma, Yifan Peng, Jinglong Yang, Qilin Sun, Yuming Fang   +5 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

Multi‐Scale Transformer for Image Restoration

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Although Transformer‐based image restoration methods have demonstrated impressive performance, existing Transformers still insufficiently exploit multiscale information. Previous non‐Transformer‐based studies have shown that incorporating multiscale features is crucial for improving restoration results.
Wuzhen Shi, Youwei Pan, Chun Zhao, Yuqing Liu, Shaobo Zhang, Heng Zhang, Yang Wen   +6 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