Given an image, detects whether there is a human face or a dog in it. In case it is a dog, the algorithm classifies the breed of the dog. Deep Learning Nanodegree project.
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Nov 4, 2020 - Jupyter Notebook
Given an image, detects whether there is a human face or a dog in it. In case it is a dog, the algorithm classifies the breed of the dog. Deep Learning Nanodegree project.
An end-to-end multi-class image classification system(web app) that classifies 101 classes of food. I'll be implementing the popular CNN architecture while utilizing the full power of transfer learning to extract features and fine-tune layers. I'll also build an interactive UI using react-js and deploy the system.
Udacity DataScience nanodegree image classifier problem
Photo sharing and photo storage services like to have location data for each photo that is uploaded. With the location data, these services can build advanced features, such as automatic suggestion of relevant tags or automatic photo organization, which help provide a compelling user experience.
Convolutional Neural Networks capable of classifying Normal vs. Pneumonia frontal chest radiograph (a set of 32 images in 8 seconds) using Transfer Learning with ResNet50
Constructed an algorithm that works on user supplied image. If a dog is detected, it estimates the breed of the dog, Trained using Transfer learning with CNN.
Facial Recognition and Tracking Application using Deep Learning.
Identifying and classifying brain tumors in MRI scans using convolutional neural networks
Content-Based Image Retrieval System using multiple images deciphers for feature extraction
An Azure based computer vision web app
Medical Diagnosis using Contrastive Learning
Transfer learning using InceptionV3 Keras model for Chest X-Ray Classification
INR Denomination Recognition is an image classification project
Behavioral Cloning (project 4 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
TFM-Lung-Disease-Classifier
Deep neural network model combining audio signal processing and pre-trained audio CNN achieved 90.1% adjusted accuracy (27.6% improvement) for classifying audio recording environment.
Waste image classification platform to promote sustainability | Created at HackMIT 2022
It is a autonomous robot equipped with sensors and cameras with deep learning algorithms to monitor and maintain crop health and act as an aid to farmers and huge estate or nursery owners
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