|
gptkbp:instance_of
|
gptkb:television_channel
|
|
gptkbp:bfsLayer
|
5
|
|
gptkbp:bfsParent
|
gptkb:Mobile_Net_V3
|
|
gptkbp:application
|
Image Classification
|
|
gptkbp:architectural_style
|
Lightweight Neural Network
|
|
gptkbp:based_on
|
Mobile Net Architecture
|
|
gptkbp:competes_with
|
gptkb:Efficient_Net
|
|
gptkbp:developed_by
|
gptkb:Job_Search_Engine
|
|
gptkbp:features
|
Quantization
Pruning
Model Compression
|
|
gptkbp:has_achievements
|
High Accuracy
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Mobile Net V4
|
|
gptkbp:improves
|
Efficiency
|
|
gptkbp:includes
|
gptkb:Batch_Normalization
|
|
gptkbp:is_adopted_by
|
gptkb:film_production_company
gptkb:Research_Institute
|
|
gptkbp:is_compatible_with
|
gptkb:Edge_TPU
gptkb:NVIDIA_Jetson
|
|
gptkbp:is_designed_for
|
Mobile and Edge Devices
|
|
gptkbp:is_evaluated_by
|
gptkb:military_unit
gptkb:COCO_Dataset
gptkb:Image_Net_Dataset
Accuracy
Memory Usage
Model Size
|
|
gptkbp:is_implemented_in
|
gptkb:Keras
gptkb:Caffe
MX Net
|
|
gptkbp:is_open_source
|
gptkb:theorem
|
|
gptkbp:is_optimized_for
|
Low Latency
|
|
gptkbp:is_part_of
|
gptkb:Mobile_Net_Family
gptkb:mobile_application
Deep Learning Frameworks
Computer Vision Tasks
|
|
gptkbp:is_supported_by
|
gptkb:municipality
gptkb:document
Community Contributions
|
|
gptkbp:is_used_for
|
Facial Recognition
Video Analysis
Gesture Recognition
Scene Understanding
|
|
gptkbp:is_used_in
|
Object Detection
Semantic Segmentation
|
|
gptkbp:performance
|
gptkb:Shuffle_Net
gptkb:Dense_Net
gptkb:Res_Net
gptkb:Squeeze_Net
|
|
gptkbp:predecessor
|
gptkb:Mobile_Net_V3
|
|
gptkbp:provides
|
Pre-trained Models
|
|
gptkbp:release_year
|
gptkb:2021
|
|
gptkbp:successor
|
gptkb:Mobile_Net_V3
|
|
gptkbp:suitable_for
|
Real-time Applications
|
|
gptkbp:supports
|
gptkb:streaming_service
|
|
gptkbp:training
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:uses
|
Depthwise Separable Convolutions
Re LU Activation Function
|
|
gptkbp:utilizes
|
Global Average Pooling
|