Core Java Projects provide integrated approach which covers all core concepts in a logical way. We conduct professional courses for students in studying undergraduate and post graduate degree courses. We developed more than 5000 core Java projects and our dedicated experts have 10+ years of experience and can designed both IEEE & Non-IEEE project concepts. We respect our unhappy customers. They are the ones who give the opportunity to do better. We organize various training programs for students like technical seminars, professional courses on programming languages, workshops, faculty training programs and so on. Most of the student’s prefers Java for their final year projects. For this reason, we allocated our world class experts to handle individual students. They are well-experienced experts with 15+ years of programming experience across many industries.
Core Java Projects
Core Java Projects is your dream destination made by us. Core Java programming is the basic of Java, once you learned core Java which carry out you for next level (advanced Java programming). We helps you to learn the Java programming concepts starting from the OOPS to Interfaces and Abstract Classes, from software package to provide API documents, from error handling to convert data into object form and other concepts such as client and server program to threads, GUI applications creation to communication and generics with database. Let us first list down our Java programming projects services,
- Java/JVM languages, JDKs …
- Combined technologies (HTML5, CSS3, JavaFX, TypeScript, Angular, LESS, JavaScript, …)
- Java frameworks (e.g. Java EE and Spring …)
- Java emerging technologies (AR, VR, IoT, Machine Learning, …)
- Java databases, IDEs, Tools, …
- Java methodologies (communication, education, agile, not agile)
- Java systems (virtualization, orchestration, distributed systems, containers, blockchain, orchestration)
Core Java Topics
- Java variables
- Java operators
- Java statement
- Access modifier
- Non access modifier
- Class and object
- Constructor
- Oops concepts
- Java API classes
- Threading
- Interface
Grab your core Java projects. You will get the complete project once you thorough with the programming concepts. Check a sample Java code in the area of “Core Java Programming”,
/* Sample Java code for Image Watermarking using OpenCV */
Supported Java Methods
- Graphics2D API (Java graphics API)
- read() & ImageIO.write() methods
- Set Color (Color c)
- setFont (Font f)
- getGraphics ()
- Drawstring (String str, int x, int y)
- drawImage (Image img, int x, int y, ImageObserver observer)
Requirements
- OpenCV 2.4
- Jdk 1.6 and later versions
// Source Code…..
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;
public class Main {
public static void main( String[] args ){
try{
System.loadLibrary( Core.NATIVE_LIBRARY_NAME );
Mat source = Highgui.imread(“digital_image_processing.jpg”, Highgui.CV_LOAD_IMAGE_COLOR);
Mat destination = new Mat(source.rows(),source.cols(), source.type());
Core.putText(source, “Tutorialspoint.com”, new Point (source.rows()/2,source.cols()/2), Core.FONT_ITALIC,new Double(1),new Scalar(255));
Highgui.imwrite(“watermarked.jpg”, source);
}
catch (Exception e) {
System.out.println(“Error: “+e.getMessage());
}
}
}
Let’s have a look at the latest Core Java Projects Titles using Java and Open CV,
- Morphological Pattern Spectrum Based Image Manipulation Detection
- Machine vision based solar panels for location and recognition
- OpenCV based fingerprint extraction and implementation
- Robotic precision farming used for Weed recognition framework
- An Improving DoD Acquisition Efficiency based on Fixed-Wing Aircraft Simulation Tool
- Hyper spectral Image Classification Method based on Cube-CNN-SVM
- 3D Intracranial Structure Deformation Features via Brain MRI Tumor Segmentation
- Computer vision based by Reduction of building façade model complexity
- Sentiment Classification of Linking Similar Feature Clusters via Transfer Learning
- Visual sensor networks used for Multi-focus image fusion
- Adaptive learning factor by Improved kernelized correlation filters tracking algorithm
- Image Set Classification based Kernel Two Dimensional Subspace
- Mid-level Features derived from High-Resolution Remote-Sensing Images for Semantic Classification
- Extract semantic mesh information from Wikipedia tables with lists
- Visual cryptography with neural networks based Security enhancement for image steganography
- Categorization of interferometric artificial aperture radar image by deep learning approach
