Results 121 to 130 of about 15,271 (229)
IEEE Open Journal of Signal ProcessingSemantic segmentation of remote sensing images is extensively used in crop cover and type analysis, and environmental monitoring. In the semantic segmentation of remote sensing images, owning to the specificity of remote sensing images, not only the ...
Rong-Xing Ding +4 more
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Efficient Wheat Disease Identification Using Hybrid Swin-SHARP Vision Model
IEEE AccessAccurate identification of wheat diseases is an essential component for increasing crop yields and guaranteeing global food security. However, subjective opinions, errors, and laborious procedures frequently limit traditional approaches, which are based ...
Waqar Khalid +3 more
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DCHT: Deep Complex Hybrid Transformer for Speech Enhancement
, 2023 Most of the current deep learning-based approaches for speech enhancement only operate in the spectrogram or waveform domain. Although a cross-domain transformer combining waveform- and spectrogram-domain inputs has been proposed, its performance can be ...
Li, Jialu +3 more
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Sounds like gambling : detection of gambling venue visitation from sounds in gamblers’ environments using a transformer [PDF]
Objective digital measurement of gamblers visiting gambling venues is conducted using cashless cards and facial recognition systems, but these methods are confined within a single gambling venue.
304901/profile-ja.html +12 more
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Swin Transformer Fusion Network for Image Quality Assessment
IEEE AccessThis paper presents an efficient deep-learning model named Swin Transformer fusion network (STFN) for full-reference image quality assessment (FR-IQA). The STFN model uses the first and second stages of the Swin Transformer for feature extraction.
Hyeongmyeon Kim, Changhoon Yim
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B-Cos Aligned Transformers Learn Human-Interpretable Features
Vision Transformers (ViTs) and Swin Transformers (Swin) are currently state-of-the-art in computational pathology. However, domain experts are still reluctant to use these models due to their lack of interpretability.
Boxberg, Melanie +9 more
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Multiscale transformer-based network for rangeland plant classification used in pasture scoring [PDF]
Rangeland ecosystems have been sources for pastoral communities. However, traditional seasonal mobility patterns are disrupted by climate change, requiring more dynamic, data-driven plant-based rangeland assessment.
Nasirahmadi, Abozar
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Deep Reinforcement Learning with Swin Transformers
Proceedings of the 2024 8th International Conference on Digital Signal ProcessingTransformers are neural network models that utilize multiple layers of self-attention heads and have exhibited enormous potential in natural language processing tasks. Meanwhile, there have been efforts to adapt transformers to visual tasks of machine learning, including Vision Transformers and Swin Transformers.
Li Meng +3 more
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UperFormer: A Multi-scale Transformer-based Decoder for Semantic Segmentation
, 2022 While a large number of recent works on semantic segmentation focus on designing and incorporating a transformer-based encoder, much less attention and vigor have been devoted to transformer-based decoders.
Gao, Pan +4 more
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SensorsDefect detection is crucial for quality control in industrial products. The defects in industrial products are typically subtle, leading to reduced accuracy in detection.
Xiaona Song +4 more
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