CS-ResNet: Cost-sensitive residual convolutional neural network for PCB cosmetic defect detection
In the printed circuit board (PCB) industry, cosmetic defect detection is an essential process
to ensure product quality. However, existing PCB cosmetic defect detection approaches …
to ensure product quality. However, existing PCB cosmetic defect detection approaches …
A novel approach for diabetic retinopathy screening using asymmetric deep learning features
Automatic screening of diabetic retinopathy (DR) is a well-identified area of research in the
domain of computer vision. It is challenging due to structural complexity and a marginal …
domain of computer vision. It is challenging due to structural complexity and a marginal …
Contextual ensemble network for semantic segmentation
Recently, exploring features from different layers in fully convolutional networks (FCNs) has
gained substantial attention to capture context information for semantic segmentation. This …
gained substantial attention to capture context information for semantic segmentation. This …
SCCGAN: style and characters inpainting based on CGAN
R Liu, X Wang, H Lu, Z Wu, Q Fan, S Li… - Mobile networks and …, 2021 - Springer
With the development of deep learning technology, many deep learning methods have been
applied to font recognition and generation. However, few studies focus on font inpainting …
applied to font recognition and generation. However, few studies focus on font inpainting …
Deep multi-scale fusion neural network for multi-class arrhythmia detection
Automated electrocardiogram (ECG) analysis for arrhythmia detection plays a critical role in
early prevention and diagnosis of cardiovascular diseases. Extracting powerful features from …
early prevention and diagnosis of cardiovascular diseases. Extracting powerful features from …
Local self-attention in transformer for visual question answering
X Shen, D Han, Z Guo, C Chen, J Hua, G Luo - Applied Intelligence, 2023 - Springer
Abstract Visual Question Answering (VQA) is a multimodal task that requires models to
understand both textual and visual information. Various VQA models have applied the …
understand both textual and visual information. Various VQA models have applied the …
Sentiment analysis of text based on bidirectional LSTM with multi-head attention
F Long, K Zhou, W Ou - IEEE Access, 2019 - ieeexplore.ieee.org
Recent years, many scientists address the research on text sentiment analysis of social
media due to the exponential growth of social multimedia content. Natural language …
media due to the exponential growth of social multimedia content. Natural language …
GCNet: Grid-like context-aware network for RGB-thermal semantic segmentation
Semantic segmentation methods can achieve satisfactory performance under poor lighting
conditions by exploiting the complementary cues in RGB and thermal images. However …
conditions by exploiting the complementary cues in RGB and thermal images. However …
Deep hierarchical encoding model for sentence semantic matching
Sentence semantic matching (SSM) always plays a critical role in natural language
processing. Measuring the intrinsic semantic similarity among sentences is very challenging …
processing. Measuring the intrinsic semantic similarity among sentences is very challenging …
Multi-scale segmentation squeeze-and-excitation UNet with conditional random field for segmenting lung tumor from CT images
Background and objective Lung cancer counts among diseases with the highest global
morbidity and mortality rates. The automatic segmentation of lung tumors from CT images is …
morbidity and mortality rates. The automatic segmentation of lung tumors from CT images is …