GitHub - forresti/SqueezeNet: SqueezeNet: AlexNet-level accuracy...
https://github.com/forresti/SqueezeNet
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters. SqueezeNet_v1./train_val.prototxt #model architecture SqueezeNet_v1./solver.prototxt #additional training details (learning rate...
[1602.07360] SqueezeNet: AlexNet-level accuracy with 50x fewer...
https://arxiv.org/abs/1602.07360
SqueezeNet achieves AlexNet-level accuracy on ImageNet with 50x fewer parameters. Additionally, with model compression techniques we are able to compress SqueezeNet to less than 0.5MB (510x...
SqueezeNet convolutional neural network - MATLAB squeezenet
https://www.mathworks.com/help/deeplearning/ref/squeezenet.html
SqueezeNet is a convolutional neural network that is 18 layers deep. You can use classify to classify new images using the SqueezeNet network. For an example, see Classify Image Using SqueezeNet.
Review: SqueezeNet (Image Classification) | Towards Data Science
https://towardsdatascience.com/review-squeezenet-image-classification-e7414825581a
In this story, SqueezeNet, by DeepScale, UC Berkeley and Stanford University, is reviewed. With equivalent accuracy, smaller CNN architectures offer at least three advantages.
SqueezeNet - YouTube
https://www.youtube.com/watch?v=ge_RT5wvHvY
This video explains the SqueezeNet architecture! This model is manually designed to reduce model size based on a set of heuristics. This results in...
SqueezeNet | PyTorch
https://pytorch.org/hub/pytorch_vision_squeezenet/
Model squeezenet1_0 is from the SqueezeNet: AlexNet-level accuracy with Model squeezenet1_1 is from the official squeezenet repo. It has 2.4x less computation and slightly fewer parameters than...
SqueezeNet — Wikipedia Republished // WIKI 2
https://wiki2.org/en/SqueezeNet
SqueezeNet. Quite the same Wikipedia. SqueezeNet was originally released on February 22, 2016.[2] This original version of SqueezeNet was implemented on top of the Caffe deep learning...
SqueezeNet Explained | Papers With Code
https://paperswithcode.com/method/squeezenet
SqueezeNet is a convolutional neural network that employs design strategies to reduce the number of parameters, notably with the use of fire modules that "squeeze" parameters using 1x1 convolutions.
SqueezeNet and MobileNet: Deep learning models for... - AI in Practice
https://aiinpractice.com/squeezenet-mobilenet/
SqueezeNet and MobileNet are two network architectures that are well suited for mobile phones and While the current trend is to make deeper and deeper networks to improve accuracy, SqueezeNet...
Notes on SqueezeNet. The paper of SqueezeNet provides... | Medium
https://medium.com/@smallfishbigsea/notes-of-squeezenet-4137d51feef4
For the same accuracy of AlexNet, SqueezeNet can be 3 times faster and 500 times smaller. The following chart shows the advantages of SqueezeNet. Comparison [1].
SqueezeNet V1.1 - Wolfram Neural Net Repository
https://resources.wolframcloud.com/NeuralNetRepository/resources/SqueezeNet-V1.1-Trained-on-ImageNet-Competition-Data
SqueezeNet V1.1 Trained on ImageNet Competition Data. Released in 2016, SqueezeNet is a successful attempt to produce a high-performance image classification model using as few...
A Guide to ResNet, Inception v3, and SqueezeNet | Paperspace Blog
https://blog.paperspace.com/popular-deep-learning-architectures-resnet-inceptionv3-squeezenet/
From left to right: SqueezeNet, SqueezeNet with simple bypass, and SqueezeNet with complex bypass. Following Strategy Two, the filters per fire module are increased with "simple bypass."
WITH
https://openreview.net/pdf?id=S1xh5sYgx
SqueezeNet: preserving accuracy with few parameters. Architectural Design Strategies. Other SqueezeNet details. Evaluation of SqueezeNet. CNN Microarchitecture Design Space Exploration.
(PDF) SqueezeNet: AlexNet-level accuracy with 50x fewer parameters...
https://www.researchgate.net/publication/301878495_SqueezeNet_AlexNet-level_accuracy_with_50x_fewer_parameters_and_05MB_model_size
SqueezeNet achieves AlexNet-level accuracy on ImageNet with 50x fewer parameters. Additionally, with model compression techniques we are able to compress SqueezeNet to less than...
Brief introduction of squeezenet / squeezenext | Develop Paper
https://developpaper.com/brief-introduction-of-squeezenet-squeezenext-lightweight-network/
Squeezenet series is a relatively early and classic lightweight network, which uses fire module for parameter compression, and squeezenext improves it by adding separation convolution.
Accelerating SqueezeNet on FPGA
https://lankas.github.io/15-618Project/
SqueezeNet was created to combat the large number of parameters required for CNNs. Demo: Simultaneously show SqueezeNet in action on multiple images with one version running the CPU...
SqueezeNet - WikiVisually
https://wikivisually.com/wiki/SqueezeNet
SqueezeNet was originally released on February 22, 2016;[2] this original version of SqueezeNet Shortly thereafter, the open-source research community ported SqueezeNet to a number of other...
Modern convnets, squeezenet, Xception, with Keras and TPUs
https://codelabs.developers.google.com/codelabs/keras-flowers-squeezenet?hl=en
What you'll learn To build a model using the squeezenet architecture To use TPUs in order to train fast and iterate on your architecture
python - SqueezeNet Problems - Stack Overflow
https://stackoverflow.com/questions/45170288/squeezenet-problems
SqueezeNet_v1.0/squeezenet_v1.0.caffemodel #pretrained model parameters. When running the first command,i get this error,I have no idea what to do?
squeezenet · GitHub Topics · GitHub
https://github.com.cnpmjs.org/topics/squeezenet
deep-learning pytorch image-classification densenet resnet squeezenet inceptionv3 googlenet resnext wideresnet cifar100 mobilenet inceptionv4 shufflenet xception nasnet inception-resnet-v2.
SqueezeNet 1.2 | Azure AI Gallery
https://gallery.azure.ai/Model/SqueezeNet-1-2-2
SqueezeNet is a light-weight convolutional network used for classification. **Paper** [SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size][1] **Dataset...
SqueezeNet fire module
https://cv-tricks.com/tensorflow-tutorial/understanding-alexnet-resnet-squeezenetand-running-on-tensorflow/
SqueezeNet is remarkable not for its accuracy but for how less computation does it need. SqueezeNet introduced a Fire module which is made of alternate Squeeze and Expand modules.
A convolutional neural network with SqueezeNet architecture
https://pypi.org/project/squeezenet/
pip install squeezenet. Copy PIP instructions. Latest version. Released: May 27, 2017. A convolutional neural network with SqueezeNet architecture.