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air-pollution-detecting-system-using-mq135-gas-sensor

an-optimized-approach-to-medical-image-classification-using-ensemble-learning-with-deep-convolution

astu_web_processing_experiment

Here, I am providing solutions for Web Processing lab experiments(from experiment 1 to experiment 10) of B.Tech 5th semesters (under ASTU)

corona-care

This is an android application which was build to spread awreness during COVID19 pandemic 2019.

covid-19_chest_x-ray_image_generation_using_gan

Covid-19 x-ray image enhancement using Histogram Equalization technique

covid-19_chest_x-ray_image_generation_using_resnet50_and_dcgan_model

This repository provides codes with datasets for the generation of synthesis images of Covid-19 Chest X-ray using DCGAN as generator and ResNet50 as discriminator from a set of raw covid-19 chest x-ray images, which are enhanced and segmented before passing through the DCGAN model.

detective_craft

Detective Craft is Minesweeper clone game using tkinter in python. Minesweeper is a single-player puzzle video game. The objective of the game is to clear a rectangular board containing hidden "mines" or bombs without detonating any of them, with help from clues about the number of neighboring mines in each field.

different_types_of_skin_cancer_detection_using_dl_models

Implemented different CNN models for the detection of different types of skin cancers. The dataset consists of 9 classes of different skin cancers along with 1 normal class & thr model have achieved an accuracy of 87.34%.

digital_journey_flipbook

face_mask_detection_using_mobilenetv2_cnn_model

Here, I have transfer learning the pre-trained MobileNet V2 CNN model to detect whether the person is wearing a mask or not

happy_birthday_tg

image_based_air_pollution_detection_using_inceptionv3_model

In this project work, the main motive is to build a deep learning model to detect air pollution from real-time images. In order to achieve that goal, we have collected data from different sources and then enhanced the low-quality images using the Image enhancement technique. Our next step was to train a CNN (Convolutional Neural Network) on the images in order to detect air pollution by analyzing the clearness of the sky in the image. In this work, we have used the Inception V3 model. After the successful testing of the CNN model, we have deployed the model on an Android Application.

know_your_dog

molten_magic_blast_furnace_flipbook

multilingual_abuse_detection

play_with_sql_queries

portfolio

pos_tagging_in_indian_languages

quantum_machine_learning

speaker-identification-using-ensemble-learning-approach-considering-cnn-as-feature-extractor

Speaker Identification Using Ensemble Learning Approach Considering CNN As Feature Extractor

stock_market_prediction_using_numerical_and_textual_analysis

Here, I have used 6 different Neural Network models to carry out the analysis & Prediction of stock price/performance and achieved 85.5% accuracy with Gradient Boosting Model.

streamlit-example

Example Streamlit app that you can fork to test out share.streamlit.io

sukonyaphukan

testing