Results 11 to 20 of about 83,465 (280)
Transformers in Remote Sensing: A Survey
Remote Sensing, 2023 Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformer-based architectures, originally introduced in natural language processing, have pervaded ...
Abdulaziz Amer Aleissaee +6 more
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Drones, 2023 The reliable and efficient large-scale mapping of date palm trees from remotely sensed data is crucial for developing palm tree inventories, continuous monitoring, vulnerability assessments, environmental control, and long-term management.
Mohamed Barakat A. Gibril +5 more
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A Survey on Vision Transformer [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Transformer, first applied to the field of natural language processing, is a type of deep neural network mainly based on the self-attention mechanism. Thanks to its strong representation capabilities, researchers are looking at ways to apply transformer to computer vision tasks.
Kai Han +12 more
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Wildfire Segmentation Using Deep Vision Transformers
Remote Sensing, 2021 In this paper, we address the problem of forest fires’ early detection and segmentation in order to predict their spread and help with fire fighting. Techniques based on Convolutional Networks are the most used and have proven to be efficient at solving ...
Rafik Ghali +4 more
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Vision Transformers for Vein Biometric Recognition
IEEE Access, 2023 In October 2020, Google researchers present a promising Deep Learning architecture paradigm for Computer Vision that outperforms the already standard Convolutional Neural Networks (CNNs) on multiple image recognition state-of-the-art datasets: Vision ...
Raul Garcia-Martin, Raul Sanchez-Reillo
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Self-Supervised Vision Transformers for Malware Detection
IEEE Access, 2022 Malware detection plays a crucial role in cyber-security with the increase in malware growth and advancements in cyber-attacks. Previously unseen malware which is not determined by security vendors are often used in these attacks and it is becoming ...
Sachith Seneviratne +3 more
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IEEE Open Journal of Intelligent Transportation Systems, 2023 In this paper, we investigate the use of Vision Transformers for processing and understanding visual data in an autonomous driving setting. Specifically, we explore the use of Vision Transformers for semantic segmentation and monocular depth estimation ...
Durga Prasad Bavirisetti +3 more
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Reversible Vision Transformers
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 We present Reversible Vision Transformers, a memory efficient architecture design for visual recognition. By decoupling the GPU memory requirement from the depth of the model, Reversible Vision Transformers enable scaling up architectures with efficient memory usage.
Mangalam, Karttikeya +6 more
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Building Extraction With Vision Transformer [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Submitted to ...
Libo Wang +3 more
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Adjustment of model parameters to estimate distribution transformers remaining lifespan [PDF]
, 2018 Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the ...
Gotay Sardiñas, Jorge +3 more
core +1 more source