Results 111 to 120 of about 15,271 (229)
DeepLOC: Deep Learning-based Bone Pathology Localization and Classification in Wrist X-ray Images
, 2023 In recent years, computer-aided diagnosis systems have shown great potential in assisting radiologists with accurate and efficient medical image analysis.
Astashev, Pavel +4 more
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Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Data [PDF]
Facing the escalating threat of global wildfires, numerous computer vision techniques using remote sensing data have been applied in this area. However, the selection of deep learning methods for wildfire prediction remains uncertain due to the lack of ...
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IEEE AccessAccurate classification of moss species is essential for progress in ecology and biology. However, traditional methods for classifying moss require significant expertise, and current deep learning techniques struggle due to limited dataset diversity and ...
Peichen Li +4 more
doaj +1 more source
, 2023 Among the current mainstream change detection networks, transformer is deficient in the ability to capture accurate low-level details, while convolutional neural network (CNN) is wanting in the capacity to understand global information and establish ...
Liu, Jia +3 more
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Transformer-based semantic segmentation for large-scale building footprint extraction from very-high resolution satellite images [PDF]
Extracting building footprints from extensive very-high spatial resolution (VHSR) remote sensing data is crucial for diverse applications, including surveying, urban studies, population estimation, identification of informal settlements, and disaster ...
A. Gibril, Mohamed Barakat +6 more
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Transformers meet CNNs for insights into breast mass classification from histopathological images
Frontiers in Artificial IntelligenceIntroductionBreast cancer remains one of the leading causes of cancer-related deaths among women worldwide, highlighting the critical need for accurate histopathological diagnosis and reliable decision-support systems to improve diagnostic sensitivity ...
Vatsala Anand, Ajay Khajuria
doaj +1 more source
Swin-Transformer has demonstrated remarkable success in computer vision by leveraging its hierarchical feature representation based on Transformer. In speech signals, emotional information is distributed across different scales of speech features, e.\,g.,
Lian, Hailun +6 more
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, 2023 Large language and vision models have transformed how social movements scholars identify protest and extract key protest attributes from multi-modal data such as texts, images, and videos.
Zhang, Yongjun
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IET Image ProcessingThe Swin‐Transformer is a variant of the Vision Transformer, which constructs a hierarchical Transformer that computes representations with shifted windows and window multi‐head self‐attention.
Yixuan Xu +3 more
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YotoR-You Only Transform One Representation
This paper introduces YotoR (You Only Transform One Representation), a novel deep learning model for object detection that combines Swin Transformers and YoloR architectures.
Loncomilla, Patricio +2 more
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