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Pedestrian detection is a subfield of object detection and plays an important role in various applications such as intelligent surveillance systems, person tracking, abnormal-scene detection, and intelligent cars.

The objective of this study is to design a convolutional neural network model which can classify images as persons or person-like from various other figures with human-like appearances.

Here, the CNN model was trained with a dataset containing images of persons and person-like objects and performed very well in both the train and validation datasets.

About the dataset

This dataset was prepared by N. J. Karthika and Saravanan Chandran. The reason for…

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The objective of this study is to classify medical images using the Convolutional Neural Network(CNN) Model.

Here, I trained a CNN model with a well-processed dataset of medical images. This model can be used to classify medical images based on categories provided as per the training dataset.

Implementation is here…

About the dataset

This dataset was developed in 2017 by Arturo Polanco Lozano. It is also known as the MedNIST dataset for radiology and medical imaging. …

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I am sure at least once in our lives every one of us watched a movie just by totally depending on the reviews. This whole process of reading quite a good number of reviews and then analyzing and categorizing them as positive, negative, or average can be tiresome and time-consuming.

What if we make our deep learning model get that done for us! Interesting right!! Let’s get to work.

This time I am training the neural nets so that at the end of the whole process my model should be able to predict ‘what is what review’. …

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Can you predict the success of a song, just by listening to it? I know! at least we try to do it many times, and a lot of times our predictions do turn out to be true. While we do consider many things and most importantly the emotions involved. Can we expect a deep learning model to predict that!?.

Of course! In this article, we will figure out how though.


We will start with importing the necessary libraries and the dataset. For my model, I am using the dataset containing 90’s songs, though I’ll link datasets…

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Human beings do have a lot of emotions and we as humans are able to distinguish between all of them. What if I tell you that we can expect some sort of same results from an ‘emotion-less machine.


In this article, we will be talking about the use of the deep learning model in classifying two different emotions at a time. However, this thing can any day be extended to multi-class classification.

In this project of mine, I have worked on Keras, and I have handpicked some images to make the dataset from scratch, feel free to use a pre-defined…

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The objective of this study is to classify various types of sports on the basis of snapshots or images of those respective sports.

This model can be used to classify sports images or snapshots as per their respective categories.

Implementation is here…

About the dataset

This dataset was developed by Gerry [Retiired Director Satcom at General Dynamics · Scottsdale, Arizona, United States] with an objective of building a clean dataset that would be easy to use and should not be containing bad or duplicate images between train, test and validation datasets.

According to Gerry, for the preparation of this dataset…

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This article presents a guide to Neural Style Transfer using Deep Learning. Neural Style Transfer is a technique of composing images in the style of another image. Neural Style Transfer takes three images as input, namely the image you want to stylise: the Content Image, a Style image, and a Combination Image, which is a copy of the Content Image initially. The technique blends the Combination Image such that it resembles the Content Image painted in the style of Style Image. …

Computer Vision for Convenient Inventory Management

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Retail especially daily needs and grocery stores have been traditional industries since quite a while now. With growing competition in terms of different competitors and increasing technological demands companies need to stay on their toes and up-to-date with innovations or risk staying behind.

This is where deep learning methods such as Computer Vision can come in and significantly change the experience for customers and businesses alike. In this blog I will make a deep learning based classification tool which can classify grocery items into different categories for easier management. This use case can have a multitude of implementations in various…

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Cancer, which is a common disease nowadays is mainly caused due to rapid growth of cancer cells inside our body. There are various types of cancers which are present such as Breast Cancer, Lung Cancer, Pancreatic Cancer etc.

Skin Cancer(Melanoma),which is mostly curable, can become deadly if not detected at an early early stage. Hence, it is important to detect which one is malignant and which one is benign.

The model proposed here , is capable to classify images based on Convolutional Neural Networks and can eventually yield good results.

Table of Contents:


>Data Preparation

>Image Processing

>Model Training

>Model Evaluation


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A gemstone (gem, fine gem, jewel, precious stone, or semi-precious stone) is a piece of mineral crystal which, in cut and polished form, is used to make jewellery or other adornments.

In this project, we will classify the gemstone based on the given image.

Dataset —

The dataset consists of 40 different kinds of gemstones. The training folder contains 40different folders, each named after a gemstone, and containing 30–40 images each.


  • Start off by importing all the required libraries
  • Download the data and unzip it to access the images and labels from your notebook.
  • There are 40…

AI Technology & Systems

Simplifying AI development for EDGE devices

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