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Multi-view heterogeneous graph learning with compressed hypergraph neural networks.

Neural networks : the official journal of the International Neural Network Society
Multi-view learning is an emerging field of multi-modal fusion, which involves representing a single instance using multiple heterogeneous features to improve compatibility prediction. However, existing graph-based multi-view learning approaches are ...

Asymmetric double-winged multi-view clustering network for exploring diverse and consistent information.

Neural networks : the official journal of the International Neural Network Society
In unsupervised scenarios, deep contrastive multi-view clustering (DCMVC) is becoming a hot research spot, which aims to mine the potential relationships between different views. Most existing DCMVC algorithms focus on exploring the consistency infor...

DECNet: Dense embedding contrast for unsupervised semantic segmentation.

Neural networks : the official journal of the International Neural Network Society
Unsupervised semantic segmentation is important for understanding that each pixel belongs to known categories without annotation. Recent studies have demonstrated promising outcomes by employing a vision transformer backbone pre-trained on an image-l...

Interpretable medical image Visual Question Answering via multi-modal relationship graph learning.

Medical image analysis
Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language Models (LLMs), aiming to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficienc...

Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation.

Neural networks : the official journal of the International Neural Network Society
Current state-of-the-art medical image segmentation techniques predominantly employ the encoder-decoder architecture. Despite its widespread use, this U-shaped framework exhibits limitations in effectively capturing multi-scale features through simpl...

CBG-Net: Cross-modality and cross-scale balance network with global semantics for multi-modal 3D object detection.

Neural networks : the official journal of the International Neural Network Society
Multi-modal 3D object detection is instrumental in identifying and localizing objects within 3D space. It combines RGB images from cameras and point-clouds data from lidar sensors, serving as a fundamental technology for autonomous driving applicatio...

Dual domain distribution disruption with semantics preservation: Unsupervised domain adaptation for medical image segmentation.

Medical image analysis
Recent unsupervised domain adaptation (UDA) methods in medical image segmentation commonly utilize Generative Adversarial Networks (GANs) for domain translation. However, the translated images often exhibit a distribution deviation from the ideal due...

Optimizing word embeddings for small dataset: a case study on patient portal messages from breast cancer patients.

Scientific reports
Patient portal messages often relate to specific clinical phenomena (e.g., patients undergoing treatment for breast cancer) and, as a result, have received increasing attention in biomedical research. These messages require natural language processin...

An informative dual ForkNet for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society
An autoencoder for video anomaly detection task is a type of algorithm with the primary purpose of learning an "informative" representation of the normal data that can be used for identifying the abnormal data by learning to reconstruct a set of inpu...

Mining core information by evaluating semantic importance for unpaired image captioning.

Neural networks : the official journal of the International Neural Network Society
Recently, exciting progress has been made in the research of supervised image captioning. However, manually annotated image-annotation pair data is difficult and expensive to obtain. Therefore, unpaired image captioning becomes an emerging challenge....