Pinned Repositories
Analyse-USElecCamp
cercatrova
Kalpana Hackathon Project
Door_Lock
An Arduino Project to operate a relay connected to an electromagnetic door lock system by means of an FPS-GT511C3 Fingerprint Scanner and an HC-05 Bluetooth module
fingerprint-mqtt
Fingerprint sensor with MQTT support based on Adafruit Fingerprint Sensor Library
forum
Web Tech and DBMS Project
INTAL_WIP
Integer Arbitrary Length
matlab_findPattern
Pattern recognition is the process of recognizing patterns by using an algorithm. Pattern recognition can be defined as the classification of data based on knowledge already gained or on statistical information extracted from patterns and their representation. One of the important aspects of the pattern recognition is its application potential. Features may be represented as continuous, discrete or discrete binary variables. A feature is a function of one or more measurements, computed so that it quantifies some significant characteristics of the object. In computer vision, speeded up robust features (SURF) is a patented local feature detector and descriptor. It can be used for tasks such as object recognition, image registration, classification, or 3D reconstruction. It is partly inspired by the scale-invariant feature transform (SIFT) descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. To detect interest points, SURF uses an integer approximation of the determinant of Hessian blob detector, which can be computed with 3 integer operations using a precomputed integral image. Its feature descriptor is based on the sum of the Haar wavelet response around the point of interest. These can also be computed with the aid of the integral image. Blob detection methods are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, compared to surrounding regions. The determinant of a Hessian matrix can be used as a generalisation of the second derivative test for single-variable functions.
Routing_Table_C
Data structure miniProject for college. IP Forwarding / Routing Table using graphs and linked lists on C programming Language.
Smart_Military_Vest
A Smart Vest for soldier at combat. This project used various sensors and communication protocols paired with an Arduino. Data reporting on IOT (Internet of Things) platform Ubidots with Heart Rate readings, Air composition (Chemicals / Bio-Warfare Detection) and two way communication among soldiers and home base were among several features implemented.
SmartEnergyMeter
Final Year Project: Code to poll smart energy meter and display it
unseemlycoder's Repositories
unseemlycoder/cercatrova
Kalpana Hackathon Project
unseemlycoder/matlab_findPattern
Pattern recognition is the process of recognizing patterns by using an algorithm. Pattern recognition can be defined as the classification of data based on knowledge already gained or on statistical information extracted from patterns and their representation. One of the important aspects of the pattern recognition is its application potential. Features may be represented as continuous, discrete or discrete binary variables. A feature is a function of one or more measurements, computed so that it quantifies some significant characteristics of the object. In computer vision, speeded up robust features (SURF) is a patented local feature detector and descriptor. It can be used for tasks such as object recognition, image registration, classification, or 3D reconstruction. It is partly inspired by the scale-invariant feature transform (SIFT) descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. To detect interest points, SURF uses an integer approximation of the determinant of Hessian blob detector, which can be computed with 3 integer operations using a precomputed integral image. Its feature descriptor is based on the sum of the Haar wavelet response around the point of interest. These can also be computed with the aid of the integral image. Blob detection methods are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, compared to surrounding regions. The determinant of a Hessian matrix can be used as a generalisation of the second derivative test for single-variable functions.
unseemlycoder/Analyse-USElecCamp
unseemlycoder/Door_Lock
An Arduino Project to operate a relay connected to an electromagnetic door lock system by means of an FPS-GT511C3 Fingerprint Scanner and an HC-05 Bluetooth module
unseemlycoder/fingerprint-mqtt
Fingerprint sensor with MQTT support based on Adafruit Fingerprint Sensor Library
unseemlycoder/forum
Web Tech and DBMS Project
unseemlycoder/INTAL_WIP
Integer Arbitrary Length
unseemlycoder/Routing_Table_C
Data structure miniProject for college. IP Forwarding / Routing Table using graphs and linked lists on C programming Language.
unseemlycoder/Smart_Military_Vest
A Smart Vest for soldier at combat. This project used various sensors and communication protocols paired with an Arduino. Data reporting on IOT (Internet of Things) platform Ubidots with Heart Rate readings, Air composition (Chemicals / Bio-Warfare Detection) and two way communication among soldiers and home base were among several features implemented.
unseemlycoder/SmartEnergyMeter
Final Year Project: Code to poll smart energy meter and display it