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1061
A Single Image Deraining Algorithm Based on Swin Transformer
Published 2023-05-01“…The latter uses Swin Transformer to capture the global information and long-distance dependencies between different pixels, in combination with residual convolution and dense connection to strengthen features learning. Finally, the derained image is obtained through a global residual convolution. …”
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1062
Linear Time Non-Local Cost Aggregation on Complementary Spatial Tree Structures
Published 2023-10-01“…Moreover, a comparison of handcrafted features and deep features learned by convolutional neural networks (CNNs) in calculating the matching cost is also provided. …”
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1063
Progressive Deep Learning Framework for Recognizing 3D Orientations and Object Class Based on Point Cloud Representation
Published 2021-09-01“…The four independent networks are linked by in-between association subnetworks that are trained to progressively map the global features learned by individual networks one after another for fine-tuning the independent networks. …”
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1064
A Combined Model of Diffusion Model and Enhanced Residual Network for Super-Resolution Reconstruction of Turbulent Flows
Published 2024-03-01“…This modification ensures the preservation of essential features learned by the SR3, while simultaneously enhancing the accuracy of the flow field. …”
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1065
Genetic Programming-Based Machine Degradation Modeling Methodology
Published 2022-01-01“…Aiming at solving this problem and visualizing informative features learned from degradation data, in this paper, a generalized machine degradation modeling methodology is proposed by integrating multiple-source fusion with genetic programming (GP). …”
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1066
Medical text classification based on the discriminative pre-training model and prompt-tuning
Published 2023-08-01“…The main idea of prompt-tuning is to transform binary or multi-classification tasks into mask prediction tasks by fully exploiting the features learned by pre-training language models. This study explores, for the first time, how to classify medical texts using a discriminative pre-training language model called ERNIE-Health through prompt-tuning. …”
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1067
MCSNet: A Radio Frequency Interference Suppression Network for Spaceborne SAR Images via Multi-Dimensional Feature Transform
Published 2022-12-01“…To remove these RFI features presented on spaceborne SAR images, we propose a multi-dimensional calibration and suppression network (MCSNet) to exploit the features learning of spaceborne SAR images and RFI. In the scheme, a joint model consisting of the spaceborne SAR image and RFI is established based on the relationship between SAR echo and the scattering matrix. …”
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1068
EDFA: Ensemble deep CNN for assessing student's cognitive state in adaptive online learning environments
Published 2023-06-01“…The ensemble models have been created by applying transfer learning to two popular pre-trained models, VGG19 and ResNet50, which can learn useful features from facial images for emotion recognition tasks. Combining the features learned by both models, the ensemble approach can achieve better performance in recognising facial emotions. …”
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1069
Infrared Target Detection Based on Interval Sampling Weighting and 3D Attention Head in Complex Scenario
Published 2023-12-01“…Furthermore, to our model, we introduce the C2f module to transfer gradient information across multiple branches. The features learned using diverse branches interact and fuse in subsequent stages, further enhancing the model’s representation ability and understanding of the target. …”
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1070
Prominent features for generation Z learning behaviour in digital society environment
Published 2017“…The analysis of prominent learning behaviour generation z with digital society environment is shown by a mapping of prominent learning behaviour generation z in digital society environment and discussion relates features learning behaviour is also being discussed.…”
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1071
Comparative Evaluation of Non-Intrusive Load Monitoring Methods Using Relevant Features and Transfer Learning
Published 2021-05-01“…Finally, we introduce new transfer learning results, which confirm the relevance and the robustness of the selected features learned from our proposed dataset when they are transferred to a larger dataset. …”
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1072
INTER-REGION TRANSFER LEARNING FOR LAND USE LAND COVER CLASSIFICATION
Published 2023-12-01“…However, there are some open questions: to what extent can the features learned in one region be transferred to another? …”
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1073
An overview of artificial intelligence in diabetic retinopathy and other ocular diseases
Published 2022-10-01“…The Inception-v3 algorithm and transfer learning concept have been applied in DR and ARMD to reuse fundus image features learned from natural images (non-medical images) to train an AI system with a fraction of the commonly used training data (<1%). …”
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1074
A Lightweight Real-Time Rice Blast Disease Segmentation Method Based on DFFANet
Published 2022-09-01“…To realize the extraction of the shallow and deep features of rice blast disease as complete as possible, a feature extraction (DCABlock) module and a feature fusion (FFM) module are designed; then, a lightweight attention module is further designed to guide the features learning, effectively fusing the extracted features at different scales, and use the above modules to build a DFFANet lightweight network model. …”
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1075
AFCANet: An adaptive feature concatenate attention network for multi-focus image fusion
Published 2023-10-01“…In the inference stage, we apply the pixel-based spatial frequency fusion rules to fuse the adaptive features learned by the encoder, which can successfully combine the texture and semantic information of the image and produce a more precise decision map. …”
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1076
MyQuran diary application development considering the proposed usability features.
Published 2022“…This study also proposes usability aspects entailing usability features, learning and engagement qualities and Islamic genre application qualities. …”
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1077
Detecting Errors with Zero-Shot Learning
Published 2022-07-01“…Due to the inadequate sampling of negative samples, the features learned by those methods may be biased. In this paper, we propose an AEGAN (Auto-Encoder Generative Adversarial Network)-based deep learning model named SAT-GAN (Self-Attention Generative Adversarial Network) to detect errors in relational datasets. …”
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1078
xViTCOS: Explainable Vision Transformer Based COVID-19 Screening Using Radiography
Published 2022-01-01“…Furthermore, we show that the features learned by our transformer networks are explainable. …”
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1079
Identifying cancer driver genes based on multi-view heterogeneous graph convolutional network and self-attention mechanism
Published 2023-01-01“…Meanwhile, we combined the fused features, the original features and the three features learned from every network through a logistic regression model to predict cancer driver genes. …”
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1080
High Frequency Component Enhancement Network for Image Manipulation Detection
Published 2024-01-01“…The main stream branch takes the RGB image as input, and aggregates the features learned from the HFAB by the proposed multi-layer fusion (MLF) in a hierarchical manner. …”
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