Results 51 to 60 of about 7,104 (161)
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
, 2022 13 pages, 3 ...
Ali Hatamizadeh +5 more
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Brain Tumor Detection using Swin Transformers
CoRR, 2023 The first MRI scan was done in the year 1978 by researchers at EML Laboratories. As per an estimate, approximately 251,329 people died due to primary cancerous brain and CNS (Central Nervous System) Tumors in the year 2020. It has been recommended by various medical professionals that brain tumor detection at an early stage would help in saving many ...
Prateek A. Meshram +2 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Easy and efficient acquisition of high-resolution remote sensing images is of importance in geographic information systems. Previously, deep neural networks composed of convolutional layers have achieved impressive progress in super-resolution ...
Jingzhi Tu +3 more
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Small Object Detection for Birds with Swin Transformer
2023 18th International Conference on Machine Vision and Applications (MVA), 2023 Object detection is the task of detecting objects in an image. In this task, the detection of small objects is particularly difficult. Other than the small size, it is also accompanied by difficulties due to blur, occlusion, and so on. Current small object detection methods are tailored to small and dense situations, such as pedestrians in a crowd or ...
Da Huo +6 more
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MV-Swin-T: Mammogram Classification with Multi-View Swin Transformer
2024 IEEE International Symposium on Biomedical Imaging (ISBI)Traditional deep learning approaches for breast cancer classification has predominantly concentrated on single-view analysis. In clinical practice, however, radiologists concurrently examine all views within a mammography exam, leveraging the inherent correlations in these views to effectively detect tumors. Acknowledging the significance of multi-view
Sushmita Sarker +3 more
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陆军军医大学学报, 2023 Objective To construct an intelligent diagnosis model for T stage of esophageal cancer based on the enhanced CT images and Swin Transformer network.
WANG Runyuan, CHEN Xingcai, WU Wei
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SwinOCSR: end-to-end optical chemical structure recognition using a Swin Transformer
Journal of Cheminformatics, 2022 Optical chemical structure recognition from scientific publications is essential for rediscovering a chemical structure. It is an extremely challenging problem, and current rule-based and deep-learning methods cannot achieve satisfactory recognition ...
Zhanpeng Xu +4 more
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Multi-Focus Microscopy Image Fusion Based on Swin Transformer Architecture
Applied Sciences, 2023 In this study, we introduce the U-Swin fusion model, an effective and efficient transformer-based architecture designed for the fusion of multi-focus microscope images.
Han Hank Xia +4 more
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DarSwin: Distortion Aware Radial Swin Transformer
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 18 pages, 12 ...
Akshaya Athwale +5 more
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An Efficient FPGA-Based Accelerator for Swin Transformer
CoRR, 2023 Since introduced, Swin Transformer has achieved remarkable results in the field of computer vision, it has sparked the need for dedicated hardware accelerators, specifically catering to edge computing demands. For the advantages of flexibility, low power consumption, FPGAs have been widely employed to accelerate the inference of convolutional neural ...
Zhiyang Liu, Pengyu Yin, Zhenhua Ren
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