Advanced Research and Applications of Deep Learning and Neural Network in Image Recognition
Materialtyp:
ArtikelUtgivningsinformation: MDPI - Multidisciplinary Digital Publishing Institute 2024Beskrivning: 1 electronic resource (212 p.)Innehållstyp: - text
- computer
- online resource
- 9783725804238
- 9783725804245
- Society and Social Sciences
- Sociology and anthropology
- Sociology
- Social theory
- 3D object detection
- CNN
- Generalized Zero-Shot Learning
- HRNet network
- MobileNetV3
- OLED
- Siamese network
- Tian-Hui 1 satellite images
- U-Net
- aerial imagery
- algorithm
- architecture improvement
- chamfer distance
- contour regularization
- convolutional neural network
- cyclic federated learning
- deep learning
- discriminative
- distribution information sharing
- dynamic channel pruning
- end-to-end deep model
- face verification
- gait parameters
- global average pooling
- global information
- head pose estimation
- image classification
- image stitching
- image unmixing
- in-screen fingerprint recognition
- knowledge distillation
- lidar point cloud
- mapping requirement
- memory access improvement
- morphological algorithm
- multi-scale residual group attention
- non-IID
- partially-shared multi-task learning
- polarization direction measurement
- pose estimation
- quadrupeds
- railway extraction
- residential area extraction
- semantic-relevant
- smoke segmentation
- transferable representation
- transformer
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This reprint aims to immerse the reader in the latest research and applications of deep learning and neural networks in image recognition. Deep learning algorithms are the major driving force behind recent advances in image classification. The success of deep learning is powered by two crucial issues: large-scale training datasets and powerful computational platforms. In most cases, the performances obtained by deep neural networks are much better than those of hand-crafted delicate image features. Yet, despite the great success of deep learning in image recognition, numerous challenges remain. This Special Issue aims to present new solutions to these challenging problems.
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eng
Freely available e-book