Mobilenet

MobileOne, Low Latency Design for Image Classification — An Improved One millisecond Mobile Backbone, MobileOne, by Apple, 2022 arXiv v1, Over 5 Citations (Sik-Ho Tsang @ Medium) Image Classification Extensive analysis of different metrics is performed by deploying several mobile-friendly networks on a mobile device. An efficient backbone MobileOne, with variants achieving an inference time under 1 ms…

Content 1.1 Introduction 1.2 Problem Statement 1.3 Real-world/Business Objectives and Constraints 2.0 Mapping the real-world problem to an ML problem 2.1 Performance Metric 3.0 DataSet 3.1 Preprocessing 4.0 Model Building 4.1 Custom CNN 4.2 Transfer Learning 4.3 MobileNet 4.4 Custom MobileNet 4.5 Model Interpretation 5.0 Deployment 5.1 Extension 6.0 Future Work …

It’s the father’s day weekend, Happy Father’s day to all… I had a great start to the day; my babies surprised me with a nice breakfast, thoughtful gift and cards :) feeling so blessed… and it’s been quite a while since i got some good dose of hacking dopamine —…

Machine Learning is prevalent in many different aspects of our day-to-day life. Many researchers in universities and research labs in big tech companies are keen on taking a step forward to make machine learning algorithms perfect. There are many metrics used to evaluate the algorithms For example Accuracy, RMSE, Precision…

Hi, This is a Python tutorial that walks through, step by step, to detect within training sports images using TensorFlow The tutorial teachs how to build the network and how to code the whole process from train images until the prediction of a sports in a new image The link for the video : https://youtu.be/xORACIVRNd4 I also shared the Python code in the video description . Enjoy Eran #Python #Mobilenet #TensorFlow

I want to show you how to set up a quick pipeline for Image Classification within this article. Therefore we want to use the MobileNet model from TensorFlow Keras. This model is a pretrained one and, as the name assumes, a model for mobile applications. It is a CNN. …

In Part 5 Series of the Transfer Learning series we have discussed the Residual Nets in depth along with hands-on application of these pre-trained neural nets in Keras and PyTorch API’s. The datasets on which these pre-trained model is trained for the ILVRC competition which is held annually and their…

An intruder detection with an OAK-D Lite camera and telegram bot — I recently bought a new camera OAK-D Lite. OAK-D Lite is a small RGB-D camera. It includes neural models and everything else, which let the computer vision enthusiast heart grow. So as I have this thing, what should I do with it? Why not build a telegram bot which sends…

Depthwise Separable Convolution을 대표적으로 사용한 논문 (단, DSC를 MobileNet에서 처음 쓴것은 아니고, Inception GoogLeNet에서도 사용함) Related Works Model Compression quantization, pruning etc pruning : unstructured pruning(웨이트 단위) / structured pruning(layer단위) 요즘은 structured pruning이 더 많이 사용되고 있음 MobileNet version - v1 : DSC - v2 : residual connections - MnasNet : platform-aware NAS, squeeze-and-excitation modules - v3 : early layer optimization + swish activation