Simplified abstract syntax tree based semantic features learning for software change prediction
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Software: Evolution and Process"
DOI: 10.1002/smr.2445
Abstract: Software change prediction aims to identify the change‐prone parts of source code, which can help software practitioners allocate resources more efficiently, increase the quality of software products, and reduce maintenance costs. In recent years, researchers… read more here.
Keywords: syntax; semantic features; software; change prediction ... See more keywords
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Forecasting"
DOI: 10.1016/j.ijforecast.2021.06.011
Abstract: Abstract It is difficult to predict the financial distress of unlisted public firms due to their longer disclosure cycle of accounting information and more inadequate continuity of market trading information compared to listed firms. In… read more here.
Keywords: unlisted public; public firms; financial distress; current reports ... See more keywords
Reconstructing meaning from bits of information
Sign Up to like & getrecommendations! Published in 2019 at "Nature Communications"
DOI: 10.1038/s41467-019-08848-0
Abstract: Modern theories of semantics posit that the meaning of words can be decomposed into a unique combination of semantic features (e.g., “dog” would include “barks”). Here, we demonstrate using functional MRI (fMRI) that the brain… read more here.
Keywords: bits information; reconstructing meaning; information; meaning bits ... See more keywords
Mouse visual cortex areas represent perceptual and semantic features of learned visual categories
Sign Up to like & getrecommendations! Published in 2021 at "Nature Neuroscience"
DOI: 10.1038/s41593-021-00914-5
Abstract: Associative memories are stored in distributed networks extending across multiple brain regions. However, it is unclear to what extent sensory cortical areas are part of these networks. Using a paradigm for visual category learning in… read more here.
Keywords: features learned; cortex; semantic features; perceptual semantic ... See more keywords
An efficient fusion detector for road defect detection
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-01399-z
Abstract: As deep learning networks deepen, detecting multi-scale subtle defects is a challenging task in road images with complex background, due to some fine features gradually disappearing, which significantly increases the difficulty of extracting these fine… read more here.
Keywords: detection; efficient fusion; road; detector ... See more keywords
Application of a graph convolutional network with visual and semantic features to classify urban scenes
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Geographical Information Science"
DOI: 10.1080/13658816.2022.2048834
Abstract: Abstract Urban scenes consist of visual and semantic features and exhibit spatial relationships among land-use types (e.g. industrial areas are far away from the residential zones). This study applied a graph convolutional network with neighborhood… read more here.
Keywords: graph convolutional; network; visual semantic; convolutional network ... See more keywords
Fine-grained flood disaster information extraction incorporating multiple semantic features
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Digital Earth"
DOI: 10.1080/17538947.2024.2448221
Abstract: ABSTRACT Flood disasters rank as the most prevalent natural calamities of the twenty-first century, incurring extensive human and economic losses globally. As a crucial source for disaster monitoring, social media data exhibits high variability and… read more here.
Keywords: information; disaster; disaster information; fine grained ... See more keywords
Geographical Scene: The Natural Unit for Geographical Analysis and Its Recognition Based on Data with Spatial and Semantic Features
Sign Up to like & getrecommendations! Published in 2025 at "Annals of the American Association of Geographers"
DOI: 10.1080/24694452.2025.2511945
Abstract: Geographical analysis often faces challenges in selecting appropriate analysis units due to spatial heterogeneity, autocorrelation, and the modifiable areal unit problem (MAUP). Traditional spatial partitioning or aggregation methods using grids, administrative zones, and traffic analysis… read more here.
Keywords: scene; geographical scene; geographical analysis; spatial semantic ... See more keywords
Graph-Based Object Semantic Refinement for Visual Emotion Recognition
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3098712
Abstract: The rich semantic information contained in images is an important clue to explore visual emotions. Therefore, exploring the correlation between visual emotion and the semantic relationship of objects, and extracting more effective semantic features through… read more here.
Keywords: emotion recognition; emotion; graph; semantic features ... See more keywords
Salient Object Detection by Spatiotemporal and Semantic Features in Real-Time Video Processing Systems
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Industrial Electronics"
DOI: 10.1109/tie.2019.2956418
Abstract: Object detection is significant for event analysis in various intelligent multimedia processing systems. Although there have been many studies conducting research in this area, effective and efficient object detection methods for video sequences are still… read more here.
Keywords: video; object detection; processing systems; salient object ... See more keywords
Pseudo-Anchors: Robust Semantic Features for Lidar Mapping in Highly Dynamic Scenarios
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2022.3223219
Abstract: Dynamic environments are challenging for anchor-free mapping using lidar in intelligent driving. This study imitates anchor-based approaches such as magnetic nails by applying novel Static Confidence Criteria (SCC) to the point-cloud semantic candidates to ensure… read more here.
Keywords: highly dynamic; anchors robust; pseudo anchors; semantic features ... See more keywords