Results 81 to 90 of about 206,029 (232)

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

DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu, Xuanyu Zhang, Xiandong Meng, Jian Zhang   +3 more
wiley   +1 more source

Classifying Deepfakes Using Swin Transformers

CoRR
3 ...
Aprille J. Xi, Eason Chen
openaire   +2 more sources

Auto‐ISC: Inter‐Sample Contrastive Learning for Automated Curve Angle Calculation From Ultrasound

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Scoliosis assessment has been increasingly supported by AI‐assisted tools, enabling more efficient and standardised clinical workflows. However, existing ultrasound‐based pipelines often suffer from limited generalisation and unstable performance.
Chen Zhang, Anh Hoang Phuc Nguyen, Yongping Zheng, Sai Ho Ling   +3 more
wiley   +1 more source

Dissecting Glioma Heterogeneity: A Deep Hybrid Graph Convolutional Network With Hinge Attention for Causal‐Effect Explainability

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Brain tumour classification is a critical task in medical imaging that requires accurate and interpretable solutions to assist in clinical decision‐making. In this paper, we present GraphConvNet‐X, a novel hybrid model that integrates convolutional neural networks (CNNs) for spatial feature extraction with graph neural networks (GNNs) that ...
Sultanul Arifeen Hamim, Mubasshar U. I. Tamim, S. M. Hasan Mahmud, M. F. Mridha, Zeyar Aung   +4 more
wiley   +1 more source

Intelligent Real‐Time Medical Image Transmission for Healthcare‐IoT via Dual‐Stage Probabilistic Restoration and Lightweight Nonlinear Encryption

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Telemedicine and healthcare‐IoT require medical image transmission that preserves diagnostic quality and confidentiality under noise, packet loss and cyber threats. Existing methods often separate restoration from security and lack real‐time efficiency.
Mohamed Amine Midoun, Meryem Hamidaoui, Mohamed Zakariya Talhaoui, Abdelkarim Smaili, Djamel Eddine Mekkaoui, Ling‐Ping Cen   +5 more
wiley   +1 more source

KLASIFIKASI PENYAKIT BATU GINJAL MENGGUNAKAN SHIFTED WINDOWS TRANSFORMER (SWIN TRANSFORMER) [PDF]

Batu ginjal adalah masalah urologi umum yang dapat menyebabkan komplikasi serius jika tidak terdeteksi sejak dini. Proses diagnosis tradisional sangat bergantung pada interpretasi manual ultrasonografi, yang rentan terhadap kesalahan dan bisa memakan ...
Prastyo, Alfian Bima
core  

Feedback‐Driven Medical Image Segmentation: Modelling on Boundary‐Sensitive Feature Preservation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurate segmentation of medical images, particularly along ambiguous lesion boundaries, plays a vital role in clinical diagnosis and treatment planning. Conventional segmentation approaches often struggle to recover fine‐grained contours due to spatial detail loss caused by convolutional downsampling and the inherent sparsity of edge features,
Jikai Yang, Ming Yang, Zhiming Li, Shenglong Chen   +3 more
wiley   +1 more source

Multi-scale capsule Swin Transformer-based method for SAR image target recognition

Tongxin xuebao
A multi-scale capsule Swin Transformer network (MSCSTN) was proposed by synergizing the semantic feature encoding of capsule units with the context feature mapping of Swin Transformer. Capsule encoding and the Swin Transformer were jointly applied to SAR
HOU Yuchao, WANG Jie, LI Hongtao, HAO Yan, DUAN Xiaoqi, HUANG Kaiwen, TIAN Youliang   +6 more
doaj  

A Wildlife Multi‐Modal Recognition Method Based on Infrared Camera Images Using MWAC

Integrative Zoology, EarlyView.
A multimodal wild wildlife classification model MWAC consists of two parts:(1) Wavelet KAN module (WDS‐KAN) for image feature extraction, and (2) Label Correlated Text Extraction module (LC‐BERT) for text feature extraction. ABSTRACT Nowadays, infrared camera technology has become an important tool for large‐scale monitoring and assessment of wildlife ...
Siming Deng, Guoxiong Zhou, Genhua Liu, Zhishu Xiao, Xiaoqun Huang, Yang Hu, Ling Gui   +6 more
wiley   +1 more source