Statements (54)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:television_channel
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:Deep_Lab
|
| gptkbp:allows |
Multi-Scale Feature Extraction
|
| gptkbp:applies_to |
gptkb:software
gptkb:Deep_Learning Autonomous Driving Facial Recognition Medical Imaging Video Analysis |
| gptkbp:benefits |
High-Resolution Images
|
| gptkbp:can_be_used_with |
gptkb:Residual_Networks
Skip Connections |
| gptkbp:developed_by |
gptkb:Job_Search_Engine
|
| gptkbp:enhances |
Feature Extraction
Model Performance |
| https://www.w3.org/2000/01/rdf-schema#label |
Atrous Convolution
|
| gptkbp:improves |
Field of View
|
| gptkbp:is_challenged_by |
Computational Complexity
Overfitting Model Interpretability Data Scarcity Real-Time Processing Requirements |
| gptkbp:is_characterized_by |
Stride
Kernel Size Dilation Rate Padding Type |
| gptkbp:is_considered_as |
State-of-the-Art Technique
|
| gptkbp:is_evaluated_by |
F1 Score
Precision Recall Pixel Accuracy Mean Intersection over Union (m Io U) |
| gptkbp:is_implemented_in |
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch |
| gptkbp:is_influenced_by |
Advancements in AI
Research in Computer Vision |
| gptkbp:is_known_for |
Dilated Convolution
|
| gptkbp:is_part_of |
Image Processing Techniques
Deep Learning Frameworks Computer Vision Algorithms Neural Network Architectures |
| gptkbp:is_related_to |
gptkb:microprocessor
Convolutional Layers |
| gptkbp:is_supported_by |
Parallel Processing
Large Datasets GPU Acceleration |
| gptkbp:is_used_in |
gptkb:FCN_(Fully_Convolutional_Networks)
gptkb:Wave_Net gptkb:Deep_Lab Semantic Segmentation |
| gptkbp:reduces |
Computational Cost
|
| gptkbp:used_in |
Object Detection
Image Segmentation |