Statements (64)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Command_Line_Interface
|
| gptkbp:can_be_used_for |
object detection
|
| gptkbp:can_be_used_with |
gptkb:API
gptkb:Tensor_Flow_Serving |
| gptkbp:customization_options |
model architecture
|
| https://www.w3.org/2000/01/rdf-schema#label |
tf.keras.applications
|
| gptkbp:includes |
gptkb:Efficient_Net
gptkb:NASNet gptkb:Mobile_Net gptkb:Dense_Net gptkb:VGG16 gptkb:Inception_V3 gptkb:Res_Net50 gptkb:Xception |
| gptkbp:is_available_on |
gptkb:Git_Hub
|
| gptkbp:is_compatible_with |
gptkb:Tensor_Flow_2.x
gptkb:cloud_services GPU acceleration |
| gptkbp:is_designed_for |
high performance
ease of use |
| gptkbp:is_integrated_with |
gptkb:board_game
|
| gptkbp:is_maintained_by |
gptkb:Google
|
| gptkbp:is_part_of |
gptkb:Tensor_Flow
gptkb:Keras_Applications Tensor Flow ecosystem |
| gptkbp:is_used_for |
gptkb:machine_learning
content moderation artificial intelligence research virtual reality applications video analysis facial recognition image segmentation social media applications e-commerce applications robotics applications security applications augmented reality applications advertising applications medical image analysis computer vision tasks feature visualization real-time image classification |
| gptkbp:is_used_in |
gptkb:academic_research
gptkb:mobile_applications self-driving cars production environments deep learning research image recognition competitions |
| gptkbp:is_used_to |
load pre-trained models
|
| gptkbp:provides |
model evaluation metrics
pre-trained models model weights model conversion tools image classification models feature extraction capabilities model loading functions model summary functions |
| gptkbp:supports |
transfer learning
multi-class classification fine-tuning image preprocessing |
| gptkbp:written_in |
gptkb:Python
|
| gptkbp:bfsParent |
gptkb:Tensor_Flow
|
| gptkbp:bfsLayer |
4
|