Pattern Recognition

Multi-views Enhanced Spatio-Temporal Adaptive Transformer for Urban Traffic Prediction.- QPDet: Queuing People Detector for Aerial Images based on Adaptive Soft Label Assignment Strategy.- Supervised Mixup: Protecting the Likely Classes for Adversarial Robustness.- IFFusion: Illumination-free Fusion Network for Infrared and Visible Images.- Infrared and visible image fusion method based on learnable joint sparse low-rank separation representation.- Glare-SNet:Unsupervised Glare Suppression Balance Network.- Learning to Detect Lithography Defects in SEM Images.- Time-aware Intent Contrastive Learning with Rare-class Sample Generator for Sequential Recommendation.- UAD-DPL: An Unknown Encrypted Attack Detection Method Based on Deep Prototype Learning.- Effects of Primary Capsule Shapes and Sizes in Capsule Networks.- ASwin-YOLO: Attention - Swin Transformers in YOLOv7 for Air-to-Air Unmanned Aerial Vehicle Detection.- Quaternion Squeeze and Excitation Networks: Mean , Variance , Skewness , Kurtosis As One Entity.- Dualswin-Ynet: A novel bimodal fusion network for ship detection in remote sensing images.- STMAE: Spatial Temporal Masked Auto-Encoder for Traffic Forecasting.- Bi-UNet:Bi-level Routing Attention Unet-shaped Network based on Explicit Visual Prompt.- Learning Dynamic Representations in Large Language Models for Evolving Data Streams.- Attend, Distill, Detect: Attention-aware Entropy Distillation for Anomaly Detection.- Pneumonia Classification in chest X-ray images using Explainable Slot-Attention Mechanism.- SegNet-ATT: Cross-Channel and Spatial Attention-Enhanced U-Net for Semantic Segmentation of Flood Affected Areas.- WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking.- Detection of Oral Potentially Malignant Lesions through Tranformer-based Segmentation Models.- ROI-Aware Dynamic Network Quantization for Neural Video Compression.- SecureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning.- TVT: Training-free Vision Transformer Search on Tiny Datasets.- One-Shot Classification is Enough for Automatic Label Mapping.- Sustainable and Explainable Neural Network for Real-Time Time Series Classification.- StressViT: Splitting and Compressing Vision Transformer through Edge-Cloud Collaboration.- Effective Layer Pruning Through Similarity Metric Perspective.- A Lightweight Measure of Classification Difficulty from Application Dataset Characteristics.- Constant Time Decision Trees and Random Forest.