Statements (64)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:machine_learning
|
| gptkbp:developed_by |
gptkb:Berkeley_Vision_and_Learning_Center
|
| gptkbp:first_released |
gptkb:2013
|
| gptkbp:has_applications_in |
gptkb:medical_imaging
gptkb:cloud_computing gptkb:robotics gptkb:smart_home_devices augmented reality e-commerce gaming industry natural language processing real-time processing data science edge computing artificial intelligence research data augmentation object detection self-driving cars transfer learning video analysis feature extraction image segmentation scene understanding advertising technology social media analysis face recognition generative models style transfer Io T applications |
| gptkbp:has_community |
active user community
contributions on Git Hub |
| gptkbp:has_documentation |
tutorials
API reference installation instructions user guide model examples |
| gptkbp:has_features |
modular architecture
command line interface pre-trained models Python interface model zoo layer-wise configuration |
| gptkbp:has_performance |
high performance
efficient memory usage optimized for speed fast training times scalable to large datasets |
| https://www.w3.org/2000/01/rdf-schema#label |
Caffe
|
| gptkbp:is_compatible_with |
gptkb:Tensor_Flow
gptkb:Py_Torch |
| gptkbp:license |
gptkb:BSD_License
|
| gptkbp:programming_language |
gptkb:C++
|
| gptkbp:supports |
GPU acceleration
multiple architectures multiple data formats |
| gptkbp:used_for |
image classification
convolutional neural networks |
| gptkbp:used_in |
gptkb:academic_research
industry applications |
| gptkbp:bfsParent |
gptkb:neural_networks
gptkb:Deep_Learning gptkb:Py_Torch gptkb:NVIDIA |
| gptkbp:bfsLayer |
4
|