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Semantics

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A Semantic-Aware Attention and Visual Shielding Network for Cloth-Changing Person Re-Identification.

IEEE transactions on neural networks and learning systems
Cloth-changing person re-identification (ReID) is a newly emerging research topic that aims to retrieve pedestrians whose clothes are changed. Since the human appearance with different clothes exhibits large variations, it is very difficult for exist...

A discrete convolutional network for entity relation extraction.

Neural networks : the official journal of the International Neural Network Society
Relation extraction independently verifies all entity pairs in a sentence to identify predefined relationships between named entities. Because these entity pairs share the same contextual features of a sentence, they lead to a complicated semantic st...

Simignore: Exploring and enhancing multimodal large model complex reasoning via similarity computation.

Neural networks : the official journal of the International Neural Network Society
Recently, the field of multimodal large language models (MLLMs) has grown rapidly, with many Large Vision-Language Models (LVLMs) relying on sequential visual representations. In these models, images are broken down into numerous tokens before being ...

Semantic prioritization in visual counterfactual explanations with weighted segmentation and auto-adaptive region selection.

Neural networks : the official journal of the International Neural Network Society
In the domain of non-generative visual counterfactual explanations (CE), traditional techniques frequently involve the substitution of sections within a query image with corresponding sections from distractor images. Such methods have historically ov...

DICCR: Double-gated intervention and confounder causal reasoning for vision-language navigation.

Neural networks : the official journal of the International Neural Network Society
Vision-language navigation (VLN) is a challenging task that requires agents to capture the correlation between different modalities from redundant information according to instructions, and then make sequential decisions on visual scenes and text ins...

Synth-CLIP: Synthetic data make CLIP generalize better in data-limited scenarios.

Neural networks : the official journal of the International Neural Network Society
Prompt learning is a powerful technique that enables the transfer of Vision-Language Models (VLMs) like CLIP to downstream tasks. However, when the prompt-based methods are fine-tuned solely on base classes, they often struggle to generalize to novel...

Modeling document causal structure with a hypergraph for event causality identification.

Neural networks : the official journal of the International Neural Network Society
Document-level event causality identification (ECI) aims to detect causal relations in between event mentions in a document. Some recent approaches model diverse connections in between events, such as syntactic dependency and etc., with a graph neura...

Automated measurement of cardiothoracic ratio based on semantic segmentation integration model using deep learning.

Medical & biological engineering & computing
The objective of this study is to investigate the efficacy of the semantic segmentation model in predicting cardiothoracic ratio (CTR) and heart enlargement and compare its consistency with the reference standard. A total of 650 consecutive chest rad...

Graph Intention Embedding Neural Network for tag-aware recommendation.

Neural networks : the official journal of the International Neural Network Society
Tag-aware recommender systems leverage the vast amount of available tag records to depict user profiles and item attributes precisely. Recently, many researchers have made efforts to improve the performance of tag-aware recommender systems by using d...

Leveraging transfer learning-driven convolutional neural network-based semantic segmentation model for medical image analysis using MRI images.

Scientific reports
Recognition and segmentation of brain tumours (BT) using MR images are valuable and tedious processes in the healthcare industry. Earlier diagnosis and localization of BT provide timely options to select effective treatment plans for the doctors and ...