Tejas Naik's repositories
Image-Alignment-and-Panoramas
Stitching different perspective images into a single smooth panorama using Laplacian Blending.
DriverDrowsiness_Detection
This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
Binary-Segmentation
An interactive semi-automatic binary segmentation model. Implemented in OpenCV 3.3.0 and Python 2.7
Face-Detection-and-Tracking
Computer Vision model to detect face in the first frame of a video and to continue tracking it in the rest of the video. This is implemented in OpenCV 3.3.0 and Python 2.7
Action-Classification-using-RNN
Using Recurrent neural networks (RNNs) to classify human actions.
Auto-Scaling-of-Application-Servers
This project demonstrates the automatic spawning of an application server (Upscaling) in cases of consistent heavy server load (eg: Heavy load on Amazon servers during festives seasons and flash sale)
GAN
Using Generative Adversarial Networks (GAN) to generate MNIST image data.
NLP
A collection of Natural Language Processing projects
Support-Vector-Machine
An implementation of MultiClass Support Vector Machine from scratch using Stochastic Gradient Descent and Quadratic Programming. Used this for Object Detection.
Action-Recognition-with-CNN
Training a CNN using 3D convolution to classify each clip as a video into action classes.
DrowsyDriverDetection
This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
GolombRuler
This project implements Constraint Satisfaction Problem (CSPs). Plain Backtracking, Backtracking + Forward Checking are used to solve CSPs.
GSoC18
Google Summer of Code'18. Open Food Facts : Brands/Label Detection.
Histograms-Filters-and-Blending
Implementing histogram equalization, low-pass and high-pass filter, and laplacian blending of images.
IOTbasedSmartHomes
This project is a seminar on "IOT based user-centric ecosystem for heterogeneous smart home environments".
LASSO-Regression
LASSO (Least Absolute Shrinkage Selector Operator) is Linear Regression with L1 Regularization.
MachineLearning
Andrew Ng's Machine Learning course assignments and mini-projects
MultiAgentPacman
Mini-max, Alpha-Beta pruning, Expectimax techniques are used to implement multi-agent pacman adversarial search.
Resume
Resume
SearchingPacman
A project that applies several Artificial Intelligence techniques such as informed state space search, reinforcement learning and probabilistic inference. Algorithms such as Depth First Search, Breadth First Search, Uniform Cost Search, A-star Search enabled the pacman to win in different game versions