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   Articles with "level feature" as a keyword



Pedestrian recognition in multi-camera networks based on deep transfer learning and feature visualization

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recommendations! Published in 2018 at "Neurocomputing"

DOI: 10.1016/j.neucom.2018.07.063

Abstract: Abstract The extensive deployment of surveillance cameras in public places, such as subway stations and shopping malls, necessitates automated visual-data processing approaches to match pedestrians across non-overlapping multiple cameras. However, due to the insufficient number… read more here.

Keywords: feature; pedestrian recognition; feature visualization; camera ... See more keywords

Learning local descriptors with multi-level feature aggregation and spatial context pyramid

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recommendations! Published in 2021 at "Neurocomputing"

DOI: 10.1016/j.neucom.2021.07.030

Abstract: Abstract Despite that efforts have shifted to learning local descriptors with convolutional neural network (CNN) from hand-crafted realm, the inherent feature hierarchy within CNN has been rarely explored. To increase both the invariant and discriminative… read more here.

Keywords: local descriptors; feature; learning local; level feature ... See more keywords

Psychophysical evaluation of individual low-level feature influences on visual attention

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recommendations! Published in 2019 at "Vision Research"

DOI: 10.1016/j.visres.2018.10.006

Abstract: ABSTRACT In this study we provide the analysis of eye movement behavior elicited by low‐level feature distinctiveness with a dataset of synthetically‐generated image patterns. Design of visual stimuli was inspired by the ones used in… read more here.

Keywords: psychophysical evaluation; level feature; low level; feature ... See more keywords

MLFA-Net: multi-level feature-aggregated network for semantic change detection in remote sensing images

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recommendations! Published in 2024 at "International Journal of Digital Earth"

DOI: 10.1080/17538947.2024.2398070

Abstract: ABSTRACT The rapid advancement in Earth observation technologies has improved the acquisition of precise data on terrestrial changes. However, traditional binary change detection (BCD) fails to satisfy the complex demands of contemporary applications. In contrast,… read more here.

Keywords: multi level; change detection; level; mlfa net ... See more keywords

MFI-Net: Multi-Level Feature Integration Network With SE-Res2Conv Encoder for Jaw Cyst Segmentation

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3400319

Abstract: Accurate segmentation of organs and lesions from medical images holds paramount importance in aiding physicians with diagnosis and monitor diseases. At present, the widespread application of deep-learning in medical image segmentation is primarily attributed to… read more here.

Keywords: segmentation; level feature; multi level; mfi net ... See more keywords

Mid-Level Feature Representation via Sparse Autoencoder for Remotely Sensed Scene Classification

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recommendations! Published in 2017 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2016.2621011

Abstract: Feature representation is a classic problem in the machine learning community due to the fact that different representations can entangle and hide more or less the different explanatory factors of variation behind the raw data.… read more here.

Keywords: scene classification; feature; feature representation; level feature ... See more keywords

Low-Level Feature Enhancement Network for Semantic Segmentation of Buildings

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recommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2022.3173626

Abstract: In recent years, convolutional neural networks (CNNs) have been widely used in extracting buildings from remote sensing images. Both semantic representation and spatial location details are crucial for this task. We propose the methods to… read more here.

Keywords: low level; level feature; semantic segmentation;

LDFCDet: Boosting 3D Object Detectors With Low-High Level Feature Crosses Using Laplace Distribution

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recommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2025.3569918

Abstract: Highly accurate 3D object detection is critical for autonomous driving and robotic sensing system. However, some objects with few foreground points significantly affect the accuracy of 3D object detection. As the network depth increases, the… read more here.

Keywords: high level; level; feature crosses; level feature ... See more keywords

Supervised High-Level Feature Learning With Label Consistencies for Object Recognition

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recommendations! Published in 2020 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2019.2955557

Abstract: Due to the large intraclass variances and complicated object distribution, recognizing objects with complex appearances and arbitrary orientations has been an active research topic and a challenging task in remote sensing fields. In this article,… read more here.

Keywords: level feature; high level; object recognition;

Adaptive Mid-Level Feature Attention Learning for Fine-Grained Ship Classification in Optical Remote Sensing Images

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recommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2024.3351874

Abstract: Ship classification in optical remote sensing images is a critical task for various maritime applications, including anti-smuggling, maritime traffic control, and maritime rescue. However, fine-grained ship classification (FGSC) is challenging due to the complex background,… read more here.

Keywords: mid level; attention; remote sensing; ship classification ... See more keywords

Semisupervised Cross-Domain Remote Sensing Scene Classification via Category-Level Feature Alignment Network

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recommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2024.3392984

Abstract: In recent years, remote sensing scene classification has obtained much attention owing to its widespread applications. Nevertheless, the existing deep learning-based scene classification methods suffer from domain shift. Given a few labeled target domain samples,… read more here.

Keywords: category level; feature alignment; remote sensing; level feature ... See more keywords