Extract a feature vector for any image and find the cosine similarity for comparison using Pytorch. I have used ResNet-18 to extract the feature vector of images. Finally a Django app is developed to input two images and to find the cosine similarity.
Created a vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM). Optimized and evaluated the model on video data from a automotive camera taken during highway driving.
Exploring an approach that bridges computer vision and natural language processing by jointly modeling the labels of sequences of noisy character images that form complete words. This is a natural problem for chain-structured CRFs
The program uses HOG and LBP features to detect human in images. First, use the HOG feature only to detect humans. Next, combine the HOG feature with the LBP feature to form an augmented feature (HOG-LBP) to detect human. A Two-Layer Perceptron (feedforward neural network) will be used to classify the input feature vector into human or no-human.
Lo scopo dell'applicazione è quello di costruire un feature vector per la predizione dei pasti in base a valori registrati da sensori di qualità dell'aria. Le feature prodotte verranno automaticamente unite a feature statistiche già presenti in alcuni files. Per la classificazione utilizzare il Knowledge Flow Enviroment di Weka impostato nel file allegato.
Design and Implementation of Random Forest algorithm from scratch to execute Pacman strategies and actions in a deterministic, fully observable Pacman Environment.
The spam classifier classifies the emails into ham or spam depending on the type of mail and based on the Naives bayes machine learning model used in the Project.
