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on February 04, 2020

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Fastest Face Detection in Matlab with source code

Overview: In this article I am going to show you the simplest and fastest method to implement a face detection code in MATLAB 2012 Things to know: Haar-like features Voila-jones Method MATLAB Basic image processing Test Image: In this article to test the code we are using the famous Lenna Image .

label2rgb| MATLAB Image Processing | Lecture#05| Converting Labeled Image into RGB Image| im2bw|

Simple Speech Recognition with Hidden Markov Model (HMM)

Implement an HMM to recognize spoken words or phrases from audio data.Speech recognition with HMM is fascinating. Here’s a simplified roadmap to get us started: Dataset Preparation : Gather a dataset of audio recordings for the words or phrases you want to recognize. You can use open-source datasets like the Common Voice dataset by Mozilla. Feature Extraction : Extract useful features from the audio recordings, typically Mel-Frequency Cepstral Coefficients (MFCCs), which represent the short-term power spectrum of sound. HMM Model Definition : Define the states and transitions for your Hidden Markov Model. Each state can represent a phoneme or part of a word. Training the HMM : Use the extracted features to train your HMM. Libraries like hmmlearn in Python can be helpful for this step. Recognition : Implement the Viterbi algorithm to find the most likely sequence of states (words or phrases) given a new audio recording. Evaluation : Test your model with new audio recordings to eva...

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VHDL tutorial learn by example | xilinx ise tutorial | nexys 3 fpga | He...

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