End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

Framework for correlating two or more well logs using feature vectors generated from CNN's in Pytorch

Takes 2 images and says how similar they are based on Euclidean distance of feature vectors

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

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.

Invariant Superpixel Features for Object Detection

Dense Bag-of-Temporal-SIFT-Words

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

image perceptual hash experiment using convolutional neural net models

Self Driving Car ND Project 5 - Vehicle Detection

Generates Caption from sample Images Using Deep Neural Networks

Vehicle detection in dash cam video

Programs 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.

Computer Vision: Vehicle Detection

Vehicle detection on images and video for Self-Driving Car Engineer Nanodegree program

Discovers new ontological categories (WordNet synsets) for words based on their lexicosyntactic patterns in Wikipedia

Calculate Entropy in R

Classify sets of images in the browser

A project on text classification

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.

Gender classification using a Spider Web Model (given by tutors).

A capstone project to predict the adoption-speed of listed pets

Creating a function that takes an image, a color space conversion, and the resolution to convert it into a feature vector

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.