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   Articles with "cnn transformer" as a keyword



Searching for Strong Lenses from DESI Legacy Surveys with a Hybrid CNN-Transformer Architecture with Self-supervised Learning

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recommendations! Published in 2025 at "Publications of the Astronomical Society of the Pacific"

DOI: 10.1088/1538-3873/ade400

Abstract: Strong gravitational lensing is a valuable tool for studying the mass distributions and structural evolution of galaxies over cosmic time. However, the rarity and complexity of strong lenses necessitate the development of automatic and efficient… read more here.

Keywords: strong lenses; self supervised; supervised learning; transformer ... See more keywords

Convolved Quality Transformer: Image Quality Assessment via Long-Range Interaction Between Local Perception

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3209810

Abstract: A hybrid architecture composed of a convolutional neural network (CNN) and a Transformer is the new trend in realizing various vision tasks while pushing the limits of learning representation. From the perspective of mechanisms of… read more here.

Keywords: interaction; image quality; quality; quality assessment ... See more keywords

A CNN-Transformer Network With Multiscale Context Aggregation for Fine-Grained Cropland Change Detection

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recommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3177235

Abstract: Nonagriculturalization incidents are serious threats to local agricultural ecosystem and global food security. Remote sensing change detection (CD) can provide an effective approach for in-time detection and prevention of such incidents. However, existing CD methods… read more here.

Keywords: change detection; change; cnn; cnn transformer ... See more keywords

Multiscale Fusion CNN-Transformer Network for High-Resolution Remote Sensing Image Change Detection

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recommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2024.3361507

Abstract: Accurate change detection using remote sensing data is crucial for understanding surface dynamics. Despite the impressive success of current convolutional neural network (CNN)-based techniques, their feature extraction and representation capabilities are limited, leading to pseudochanges… read more here.

Keywords: detection; change detection; remote sensing; network ... See more keywords

DECT: Diffusion-Enhanced CNN–Transformer for Multisource Remote Sensing Data Classification

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recommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2024.3479212

Abstract: Methods for joint classification of hyperspectral images (HSIs) with high dimensionality and spectral correlation and other sensor data (e.g., optical, infrared, radar, etc.) are important directions in the field of remote sensing. To better learn… read more here.

Keywords: enhanced cnn; diffusion enhanced; remote sensing; transformer ... See more keywords

SCTNet: A Shallow CNN–Transformer Network With Statistics-Driven Modules for Cloud Detection

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recommendations! Published in 2025 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2025.3561004

Abstract: Existing cloud detection methods often rely on deep neural networks, leading to excessive computational overhead. To address this, we propose a shallow convolutional neural network (CNN)–Transformer hybrid architecture that limits the maximum downsampling rate to… read more here.

Keywords: statistics driven; cloud detection; transformer; cnn transformer ... See more keywords

CT-PromptSAM: Collaborative Prompting With Hybrid CNN–Transformer for Remote Sensing Semantic Segmentation

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recommendations! Published in 2025 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2025.3612187

Abstract: Remote sensing (RS) semantic segmentation (SS) faces critical challenges in small-object detection and boundary precision due to scale variation and complex scenes. This letter proposes CT-PromptSAM, a specialist–generalist framework integrating a CNN–Transformer specialist network and… read more here.

Keywords: remote sensing; sensing semantic; semantic segmentation; cnn transformer ... See more keywords

Counting Varying Density Crowds Through Density Guided Adaptive Selection CNN and Transformer Estimation

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recommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2022.3208714

Abstract: In real-world crowd counting applications, the crowd densities in an image vary greatly. When facing density variation, humans tend to locate and count the targets in low-density regions, and reason the number in high-density regions.… read more here.

Keywords: density regions; adaptive selection; density; cnn transformer ... See more keywords

Life Prediction of IGBT Across Working Condition via a CNN-Transformer Network

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recommendations! Published in 2025 at "IEEE Transactions on Device and Materials Reliability"

DOI: 10.1109/tdmr.2025.3567107

Abstract: Insulated Gate Bipolar Transistors (IGBTs) are extensively utilized in a multitude of fields owing to their proficiency in power conversion and their dependable operation. Anticipating the service life of IGBTs to preemptively mitigate the repercussions… read more here.

Keywords: network; methodology; life; cnn transformer ... See more keywords

Asymmetric Cross-Attention Hierarchical Network Based on CNN and Transformer for Bitemporal Remote Sensing Images Change Detection

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recommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2023.3245674

Abstract: As an important task in the field of remote sensing (RS) image processing, RS image change detection (CD) has made significant advances through the use of convolutional neural networks (CNNs). The transformer has recently been… read more here.

Keywords: cross attention; remote sensing; cnn transformer; transformer ... See more keywords

SonarNet: Hybrid CNN-Transformer-HOG Framework and Multifeature Fusion Mechanism for Forward-Looking Sonar Image Segmentation

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

DOI: 10.1109/tgrs.2024.3368659

Abstract: Forward-looking sonar (FLS) image segmentation plays a significant role in ocean engineering. However, the existing image segmentation algorithms present difficulties in extracting features from FLS images with weak semantic information, complex backgrounds, and strong environmental… read more here.

Keywords: segmentation; image; fusion; sonarnet ... See more keywords