AIMC Topic: Semantics

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Nonlinear Spiking Neural Systems for Thermal Image Semantic Segmentation Networks.

International journal of neural systems
Thermal and RGB images exhibit significant differences in information representation, especially in low-light or nighttime environments. Thermal images provide temperature information, complementing the RGB images by restoring details and contextual ...

FDC: Feature Dropout Consistency for unsupervised domain adaptation semantic segmentation.

Neural networks : the official journal of the International Neural Network Society
In Unsupervised Domain Adaptation Semantic Segmentation (UDASS), while self-training techniques have become one of the most effective methods to date, the absence of target labels makes models susceptible to overfitting. To address this problem, cons...

Replacing non-biomedical concepts improves embedding of biomedical concepts.

PloS one
Embeddings are semantically meaningful representations of words in a vector space, commonly used to enhance downstream machine learning applications. Traditional biomedical embedding techniques often replace all synonymous words representing biologic...

Paraphrase detection for Urdu language text using fine-tune BiLSTM framework.

Scientific reports
Automated paraphrase detection is crucial for natural language processing (NL) applications like text summarization, plagiarism detection, and question-answering systems. Detecting paraphrases in Urdu text remains challenging due to the language's co...

Semi-Supervised Echocardiography Video Segmentation via Adaptive Spatio-Temporal Tensor Semantic Awareness and Memory Flow.

IEEE transactions on medical imaging
Accurate segmentation of cardiac structures in echocardiography videos is vital for diagnosing heart disease. However, challenges such as speckle noise, low spatial resolution, and incomplete video annotations hinder the accuracy and efficiency of se...

Visuomotor Navigation for Embodied Robots With Spatial Memory and Semantic Reasoning Cognition.

IEEE transactions on neural networks and learning systems
The fundamental prerequisite for embodied agents to make intelligent decisions lies in autonomous cognition. Typically, agents optimize decision-making by leveraging extensive spatiotemporal information from episodic memory. Concurrently, they utiliz...

Ex2Vec: Enhancing assembly code semantics with end-to-end execution-aware embeddings.

Neural networks : the official journal of the International Neural Network Society
Binary code similarity detection (BSCD), whose goal is to identify and analyze similar or identical functions in compiled binaries, is an essential task in computer security. Recent methods leveraging deep neural networks (DNN) for numerical vector r...

SSSLN:Multivariate Time Series Forecasting via Collaborative Dynamic Graph Learning.

Neural networks : the official journal of the International Neural Network Society
Multivariate time series (MTS) forecasting has achieved notable progress through graph modeling. However, existing approaches often face two key challenges. First, traditional dynamic graph learning (DGL) methods typically maintain dynamic graphs dir...

Layer Frozen Multi-Net & Latent Space Feature-Concealed Backdoor Samples Detection.

Neural networks : the official journal of the International Neural Network Society
Identifying feature-concealed backdoor samples that entangle with benign semantics of target-class or possess dynamic triggers challenges backdoor attack detection. Existing methods focus on sample distribution differences in latent space of victim m...

TMNRED, A Chinese Language EEG Dataset for Fuzzy Semantic Target Identification in Natural Reading Environments.

Scientific data
Semantic understanding is central to advanced cognitive functions, and the mechanisms by which the brain processes language information are still being explored. Existing EEG datasets often lack natural reading data specific to Chinese, limiting rese...