MATLAB is a multi-paradigm numerical computing environment and fourth-generation programming language. A proprietary programming language developed by MathWorks, MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. MATLAB is a high-performance language for technical computing. It integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation. MATLAB can be used in projects such as modeling energy consumption to build smart power grids, developing control algorithms for hypersonic vehicles, analyzing weather data to visualize the track and intensity of hurricanes, and running millions of simulations to pinpoint optimal dosing for antibiotics.

We at Rapid Techs, provide informative introduction for understanding architectural issues and solutions to develop skills in the field of MATLAB technology. Being an academic project centre, we train you to be an engineer, who implement pragmatic approaches for solving problems, which, in a world with limited resources (in particular time and money), means minimizing the “time to solution”.

 

Some of the featured IEEE Research projects are listed below

2015 IEEE Transactions

Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose

Image Denoising by Exploring External and Internal Correlations

Image Quality Assessment for Fake Biometric Detection Application to Iris, Fingerprint,and Face Recognition

Multi-task Pose-Invariant Face Recognition

Weighted Guided Image Filtering

Continuous Depth Map Reconstruction From Light Fields

Double Line Image Rotation

Adaptive Metric Learning for Saliency Detection

Removing Camera Shake via Weighted Fourier Burst Accumulation

Compressive Bilateral Filtering

Progressive Halftone Watermarking Using Multilayer Table Lookup Strategy

Multiview Alignment Hashing for Efficient Image Search

Saliency-Based Color Accessibility

On Local Prediction Based Reversible Watermarking

Sorted Consecutive Local Binary Pattern for Texture Classification

PISA Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures With Edge-Preserving Coherence

Latent Fingerprint Enhancement via Multi-Scale Patch Based Sparse Representation

Steganography Using Reversible Texture Synthesis

Projection-Based Polygonality Measurement

Featured Projects

Effective Contrast-Based Dehazing for Robust Image Matching

Mixed Noise Removal by Weighted Encoding With Sparse Nonlocal Regularization

Hierarchical Prediction and Context Adaptive Coding for Lossless Color Image Compression

An Advanced Moving Object Detection Algorithm

Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation

A New Secure Image Transmission Technique via Secret-Fragment-Visible Mosaic Images by Nearly Reversible Color Transformations

 

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Write to us – rapidtechs@gmail.com

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