Explainable Two-Stage Xception-Swin Transformer Learning for Body-Part-Aware Fracture Detection in Musculoskeletal X-Rays. [PDF]
Shah SBH +8 more
europepmc +1 more source
Under the framework of precision agriculture, machine learning technology enables better crop handling, increased agricultural output, and reduced harm to the environment (Liakos et al., 2018).
Mehendale, Nachiket Anil
core +1 more source
Deep Learning Based on Swin-Transformer and 3D U-Net: Implant Three-Dimensional Position Planning. [PDF]
Shen J +7 more
europepmc +1 more source
Reidentifikasi Orang pada Data Parsial menggunakan Klasifier Swin Transformer
Penelitian ini dilatarbelakangi oleh kebutuhan untuk mengembangkan sistem reidentifikasi orang yang efektif dalam situasi di mana hanya data parsial tersedia, seperti dalam pengawasan keamanan di area publik atau lalu lintas.
Soemarso, Bayuadi Prakoso
core
YOLOv13-SwinTongue: Tongue Coating Diagnosis Using an Enhanced YOLOv13 with Swin Transformer. [PDF]
Yang X +5 more
europepmc +1 more source
Dual-SwinOrd: A Dual-Head Swin Transformer with Semantic Prior Injection for Ordinal Diabetic Retinopathy Grading. [PDF]
Yu W, Si X, Zhong J.
europepmc +1 more source
Retraction Note: Plant disease recognition using residual convolutional enlightened Swin transformer networks. [PDF]
Kalpana P +4 more
europepmc +1 more source
IoT-Based Monitoring and Prediction of Water Quality Using Swin-Transformer and Depthwise Separable Convolutional Neural Network Optimized by Circulatory System-Based Optimization. [PDF]
Gunti NR, Subrahmanyam K.
europepmc +1 more source
HASwinNet: A Swin Transformer-Based Denoising Framework with Hybrid Attention for mmWave MIMO Systems. [PDF]
Han X, Tu H, Ying J, Chen J, Xing Z.
europepmc +1 more source
Dual-stream token fusion with Swin Transformer and lesion-aware tokens for gastric metaplasia classification in IoMT-assisted deployment. [PDF]
Rokhsati H +3 more
europepmc +1 more source

