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gptkbp:instance_of
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gptkb:neural_networks
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gptkbp:architecture
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Lightweight
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gptkbp:available_in
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gptkb:Caffe_framework
Tensor Flow framework
Py Torch framework
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gptkbp:developed_by
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gptkb:Alexey_Dosovitskiy
gptkb:Forest_Agostinelli
gptkb:Deep_Scale
Dmitry Kolesnikov
Trevor Darrell
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gptkbp:has_applications_in
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gptkb:Autonomous_Vehicles
Object Detection
Facial Recognition
Image Segmentation
Medical Imaging
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gptkbp:has_function
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1.24 million
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gptkbp:has_input_size
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227x227 pixels
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gptkbp:has_output_size
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1000 classes
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gptkbp:has_variants
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gptkb:Squeeze_Net_1.0
gptkb:Squeeze_Net_1.1
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|
https://www.w3.org/2000/01/rdf-schema#label
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Squeeze Net
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gptkbp:influenced_by
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gptkb:Alex_Net
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gptkbp:initiated_by
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Re LU
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gptkbp:is_analyzed_in
|
gptkb:stage_adaptation
gptkb:Neural_Architecture_Search
Model Compression
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gptkbp:is_benchmarking_model_for
|
Computer Vision Tasks
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gptkbp:is_compared_to
|
gptkb:Mobile_Net
gptkb:Res_Net
gptkb:VGGNet
gptkb:Alex_Net
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|
gptkbp:is_evaluated_by
|
gptkb:CIFAR-10
gptkb:Pascal_VOC
gptkb:SVHN
gptkb:COCO
gptkb:MNIST
gptkb:CIFAR-100
Image Net validation set
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gptkbp:is_implemented_in
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gptkb:C++
gptkb:Python
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gptkbp:is_influenced_by
|
gptkb:Goog_Le_Net
gptkb:VGGNet
gptkb:Alex_Net
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|
gptkbp:is_known_for
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gptkb:Speed
Efficiency
High Accuracy
Low Memory Usage
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|
gptkbp:is_open_source
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gptkb:True
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|
gptkbp:is_optimized_for
|
gptkb:mobile_devices
Mobile and embedded devices
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|
gptkbp:is_part_of
|
gptkb:Computer_Vision
Deep Learning Models
CNN Family
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gptkbp:is_supported_by
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gptkb:Tensor_Flow
gptkb:Keras
gptkb:NVIDIA_GPUs
gptkb:Intel_CPUs
gptkb:Py_Torch
gptkb:ARM_processors
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|
gptkbp:is_trained_in
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gptkb:Image_Net_dataset
gptkb:Image_Net_Dataset
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gptkbp:is_used_in
|
gptkb:Telecommunications
gptkb:drones
gptkb:robotics
gptkb:smart_home_devices
Environmental monitoring
Image Classification
Autonomous vehicles
Fashion industry
Image segmentation
Security surveillance
Feature extraction
Augmented reality applications
Sports analytics
Gaming industry
Real-time applications
Social media applications
Manufacturing automation
Object detection
Retail analytics
Agriculture technology
Healthcare imaging
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gptkbp:is_used_in_industry_for
|
gptkb:Augmented_Reality
gptkb:virtual_reality
gptkb:drones
Smart Cameras
Real-time Image Processing
|
|
gptkbp:license
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Apache License 2.0
|
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gptkbp:model
|
<0.5 MB
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|
gptkbp:notable_feature
|
Small model size
|
|
gptkbp:orbital_period
|
50x Fewer Parameters than Alex Net
|
|
gptkbp:performance
|
Model compression techniques
Alex Net-level Accuracy
Top-5 accuracy of 57.5% on Image Net
|
|
gptkbp:primary_use
|
Image Classification
|
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gptkbp:release_year
|
gptkb:2016
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|
gptkbp:successor
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gptkb:Squeeze_Net_1.1
|
|
gptkbp:uses
|
Fire modules
|
|
gptkbp:uses_fire_modules
|
gptkb:True
|
|
gptkbp:uses_global_average_pooling
|
gptkb:True
|
|
gptkbp:uses_pooling
|
Global Average Pooling
|
|
gptkbp:year_established
|
gptkb:2016
|
|
gptkbp:bfsParent
|
gptkb:Google_Net
gptkb:Inception-v2
|
|
gptkbp:bfsLayer
|
6
|