Deep Learning Methods for Object Detection


In this article, I will explain some of the state-of-art Deep Learning Methods for Object Detection. In order to perform image analysis, it is necessary to find out all the objects that the given image contains.

Region-Based Convolution Neural Network

In general, Region-Based Convolution Neural Network (R-CNN) works as follows.

  1. At first, it divides the whole image into regions. In fact, it creates a large number of regions. Further, it checks whether any of the regions contains an object.
  2. After that RCNN performs a selective search. In order to detect an object, RCNN identifies four regions – size, textures, colors, and shapes.
  3. Further, it combines similar regions to create a larger region.

Single-Shot Detector (SSD)

In a similar manner, the Single-Shot Detector (SSD) detects multiple objects. Like the YOLO algorithm, it also applies a single shot. In order to detect bounding boxes and classes, it only takes feature maps into consideration. Also, it uses the standard CNN and performs a single pass to it. However, unlike YOLO, it makes use of varying aspect ratios in multi boxes. As can be seen, it is the fastest algorithm and achieves great accuracy. But feature loss in deep layers is a problem.

Spatial Pyramid Pooling (SPP)

Basically, SPP is a pooling layer. Thus, with the use of SPP, CNN no longer requires a fixed-size image. Hence, SPP removes the fixed-sized image constraint. In fact, the SPP layer itself generates the fixed-length outputs by pooling the features.

While the SPP-Net is a CNN architecture that makes use of the SPP layer. Although it is based on RCNN, it is much faster than RCNN.

Python Based Deep Learning Methods for Object Detection

The following list provides some of the Python Based Deep Learning Methods for Object Detection.

  • In general, we can use the package called Keras for Deep Learning. Particularly, we can install the mask-rcnn library for object detection.
  • In order to perform object detection from scratch, we can use the TensorFlow package of python.
  • Another important Deep Learning technique for object detection is YOLO (You Only Look Once) algorithm.
  • Apart from the above important libraries, python also has one more library for object detection named ImageAI.

Further Reading

Deep Learning Tutorial

Text Summarization Techniques

How to Implement Inheritance in Python

Find Prime Numbers in Given Range in Python

Running Instructions in an Interactive Interpreter in Python

Deep Learning Practice Exercise

Python Practice Exercise

Deep Learning Methods for Object Detection

Understanding YOLO Algorithm

What is Image Segmentation?

ImageNet and its Applications

Image Contrast Enhancement using Histogram Equalization

Transfer Learning and its Applications

Examples of OpenCV Library in Python

Examples of Tuples in Python

Python List Practice Exercise

Understanding Blockchain Concepts

Edge Detection Using OpenCV

Predicting with Time Series

Example of Multi-layer Perceptron Classifier in Python

Measuring Performance of Classification using Confusion Matrix

Artificial Neural Network (ANN) Model using Scikit-Learn

Popular Machine Learning Algorithms for Prediction

Long Short Term Memory – An Artificial Recurrent Neural Network Architecture

Python Project Ideas for Undergraduate Students

Creating Basic Charts using Plotly

Visualizing Regression Models with lmplot() and residplot() in Seaborn

Data Visualization with Pandas

A Brief Introduction of Pandas Library in Python

A Brief Tutorial on NumPy in Python


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