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Sobhan Shukueian
Sobhan Shukueian

13 Followers

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Information Theory — Entropy

Information Theory A cornerstone of information theory is the idea of quantifying how much information there is in a message. More generally, this can be used to quantify the information in an event and a random variable, called entropy and is calculated using probability. Calculating information and entropy is a useful tool in…

Math

5 min read

Information Theory — Entropy
Information Theory — Entropy
Math

5 min read


Jan 28, 2022

R-CNN Family

R-CNN 1 — R-CNN takes an input image, extracts around 2000 bottom-up region proposals, These proposed regions are usually selected at multiple scales with different shapes and sizes. Each region proposal will be labeled with a class and a ground-truth bounding box. 2 — Computes features for each proposal using a large…

R Cnn

5 min read

R-CNN Family
R-CNN Family
R Cnn

5 min read


Jan 27, 2022

Divergence

KL divergence To measure the difference between two probability distributions over the same variable x, a measure, called the Kullback-Leibler divergence, or simply, the KL divergence has been popularly used in the data mining literature. The concept was originated in probability theory and information theory. The KL divergence, which is closely related to…

3 min read

3 min read


Jan 23, 2022

Mask R-CNN

Overview Adding a branch for predicting an object mask in parallel. ROI Alignment instead of ROI Pooling. Architecture Mask R-CNN, extends Faster R-CNN by adding a branch for predicting segmentation masks on each Region of Interest (RoI), in parallel with the existing branch for classification and bounding box regression. …

2 min read

Mask R-CNN
Mask R-CNN

2 min read


Jan 8, 2022

Faster R-CNN Object Detection with Region Proposal Networks

Architecture The Faster R-CNN architecture consists of the RPN as a region proposal algorithm and the Fast R-CNN as a detector network. First of all, the model gets the input image and through the backbone CNN gets the feature map. Besides test time efficiency, another key reason using an RPN as…

Object Detection

5 min read

Faster R-CNN Object Detection with Region Proposal Networks
Faster R-CNN Object Detection with Region Proposal Networks
Object Detection

5 min read


Jan 7, 2022

Fast R-CNN

Overview Apply fully Convolutional networks to the whole image. ROI Pooling: each proposal is pooled into a fixed-size feature map. Classification with a softmax layer. Regression-based bounding box refinement. Architecture A Fast R-CNN network takes as input an entire image and a set of object proposals. 1. The network first processes the…

Object Dete

5 min read

Fast R-CNN
Fast R-CNN
Object Dete

5 min read


Dec 31, 2021

R-CNN Object Detection and Semantic Segmentation

Requirements Some Requirements that is needed in the main architecture of R-CNN if you are familiar with them you can skip this part :) IOU Intersection over Union (IoU) is used when calculating mAP. It is a number from 0 to 1 that specifies the amount of overlap between the predicted and…

Object Detection

4 min read

R-CNN Object Detection and Semantic Segmentation
R-CNN Object Detection and Semantic Segmentation
Object Detection

4 min read


Nov 15, 2021

Prune Deep Networks

What is Pruning And Why we need it? By increasing amounts of data and computational power, deep learning models have become bigger and deeper to better learn from data. Deploying these large, accurate models to resource-constrained computing environments such as mobile phones, smart cameras, etc poses a few key challenges. Confronting these challenges, a growing body of work has emerged…

Deeplearing

6 min read

Prune Deep Networks
Prune Deep Networks
Deeplearing

6 min read


Nov 15, 2021

Database Basics

Why Use a Database Instead of the File System? Data redundancy — wasted space Update issues — every copy of the data needs to be modified Data inconsistency — sometimes every copy is not modified Data access issues — getting to just the right data Data isolation — pulling all the data from disparate sources together Integrity constraints buried…

Databas

3 min read

Database Basics
Database Basics
Databas

3 min read


Nov 12, 2021

Residual Networks

In this post, we will learn about residual networks, why we need them, and … Why We need Residuals? Network depth has crucial importance, But Is learning better networks as easy as stacking more layers? This was answered in Deep Residual Learning for Image Recognition paper when you try to add more layers and go…

Deep Learning

4 min read

Residual Nets
Residual Nets
Deep Learning

4 min read

Sobhan Shukueian

Sobhan Shukueian

13 Followers

…. is every Where!

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