|
gptkbp:instance_of
|
gptkb:television_channel
|
|
gptkbp:bfsLayer
|
4
|
|
gptkbp:bfsParent
|
gptkb:Inception_Network
|
|
gptkbp:adapted_into
|
Real-time applications
|
|
gptkbp:architectural_style
|
gptkb:Deep_Learning
|
|
gptkbp:coat_of_arms
|
48
|
|
gptkbp:contains
|
Inception modules
|
|
gptkbp:developed_by
|
gptkb:Job_Search_Engine
Collaborative efforts
|
|
gptkbp:features
|
Asymmetric convolutions
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Inception-v4
|
|
gptkbp:improves
|
gptkb:Inception-v3
|
|
gptkbp:introduced
|
gptkb:2016
|
|
gptkbp:is_adopted_by
|
Industry applications
|
|
gptkbp:is_available_on
|
gptkb:archive
|
|
gptkbp:is_compared_to
|
gptkb:Res_Net
|
|
gptkbp:is_compatible_with
|
gptkb:Keras
|
|
gptkbp:is_designed_for
|
Large-scale image classification
|
|
gptkbp:is_documented_in
|
Research papers
|
|
gptkbp:is_enhanced_by
|
Data Augmentation
|
|
gptkbp:is_evaluated_by
|
gptkb:CIFAR-10
Cross-validation
Precision and Recall
Top-1 accuracy
Benchmark datasets
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
|
|
gptkbp:is_influenced_by
|
gptkb:Inception-v2
|
|
gptkbp:is_integrated_with
|
AI platforms
|
|
gptkbp:is_known_for
|
Scalability
High accuracy
|
|
gptkbp:is_optimized_for
|
gptkb:CEO
|
|
gptkbp:is_part_of
|
gptkb:viewpoint
gptkb:Inception_family_of_models
AI research initiatives
|
|
gptkbp:is_popular_in
|
gptkb:Research_Institute
|
|
gptkbp:is_recognized_for
|
Innovative architecture
State-of-the-art performance
|
|
gptkbp:is_related_to
|
gptkb:Deep_Residual_Networks
|
|
gptkbp:is_supported_by
|
Community contributions
NVIDIAGP Us
|
|
gptkbp:is_tested_for
|
Large datasets
Other CNN architectures
Adversarial examples
Visual Recognition tasks
|
|
gptkbp:is_used_by
|
AI researchers
|
|
gptkbp:is_used_for
|
Image Classification
|
|
gptkbp:is_used_in
|
Computer Vision tasks
|
|
gptkbp:is_utilized_in
|
Autonomous vehicles
Medical Imaging
Feature extraction
Facial recognition systems
|
|
gptkbp:performance
|
gptkb:Image_Net_competition
Object Detection
Image segmentation
Top-5 accuracy of 3.08% on Image Net
|
|
gptkbp:supports
|
gptkb:streaming_service
|
|
gptkbp:training
|
gptkb:Image_Net_dataset
Stochastic Gradient Descent
|
|
gptkbp:utilizes
|
gptkb:Batch_Normalization
|
|
gptkbp:written_in
|
gptkb:Library
|