NASNet

GPTKB entity

Statements (54)
Predicate Object
gptkbp:instance_of gptkb:neural_networks
gptkbp:achieves_top1_accuracy 82.7% on Image Net
gptkbp:achieves_top5_accuracy 95.2% on Image Net
gptkbp:adapted_into different tasks
gptkbp:based_on neural architecture search
gptkbp:competes_with other architectures like Res Net
gptkbp:consists_of convolutional layers
gptkbp:developed_by gptkb:Google
advanced algorithms
gptkbp:has_achieved state-of-the-art performance
gptkbp:has_variants gptkb:NASNet-A
gptkb:NASNet-B
gptkb:NASNet-C
https://www.w3.org/2000/01/rdf-schema#label NASNet
gptkbp:inspired_by human-designed architectures
gptkbp:introduced_in gptkb:2017
gptkbp:is_cited_in numerous academic papers
gptkbp:is_compared_to gptkb:Inception
gptkb:Dense_Net
gptkb:VGGNet
gptkbp:is_considered_as a breakthrough in neural architecture search
gptkbp:is_documented_in research papers
gptkbp:is_evaluated_by gptkb:Google_Brain_team
gptkb:CIFAR-10_dataset
gptkb:Image_Net_dataset
gptkb:CIFAR-100_dataset
gptkbp:is_implemented_in gptkb:Tensor_Flow
gptkbp:is_influenced_by evolution of neural networks
gptkbp:is_integrated_with cloud computing platforms
gptkbp:is_known_for high accuracy
flexibility in architecture design
efficient architecture search
gptkbp:is_optimized_for gptkb:mobile_devices
gptkbp:is_part_of gptkb:machine_learning
deep learning frameworks
AI research advancements
gptkbp:is_popular_in gptkb:scientific_community
gptkbp:is_recognized_by AI practitioners
gptkbp:is_supported_by community contributions
hardware accelerators
gptkbp:is_tested_for various benchmarks
gptkbp:is_trained_in large-scale datasets
gptkbp:is_used_in real-world applications
transfer learning
computer vision tasks
gptkbp:is_utilized_in gptkb:medical_imaging
gptkb:vehicles
image recognition systems
facial recognition systems
object detection systems
gptkbp:used_for image classification
gptkbp:utilizes reinforcement learning
gptkbp:bfsParent gptkb:tf.keras.applications
gptkbp:bfsLayer 5