Results 111 to 120 of about 600 (157)
Neural network based AI model for lung health assessment. [PDF]
Sci RepHassan U, Singhal A, Gupta G.
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Propeller Fault Classification for Unmanned Aerial Vehicles and Explainable Artificial Intelligence-Based Feature-Model Matching. [PDF]
Sensors (Basel)Seçkin AÇ.
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Mel-frequency cepstrum coefficient analysis of infant cry with hypothyroidism
2009 5th International Colloquium on Signal Processing & Its Applications, 2009This paper presents a new method for the analysis of newborn infant cry to detect hypothyroidism. Hypothyroidism is a condition caused by insufficient production of thyroid hormone by the thyroid gland. The proposed technique is robust as it automatically extracts and analyzes features of infant cry signal.
Rohilah Sahak +2 more
exaly +2 more sources
Perturbation analysis of mel-frequency cepstrum coefficients
2010 International Conference on Audio, Language and Image Processing, 2010Mel-frequency cepstrum coefficient (MFCC) is a widely used feature vector in speech signal precessing. Its feature extraction procedure can be seen as a mapping function which transfers the input speech signals to output MFCC feature vectors. However, this function is too complex to analyze and even a simple approximation is not easy to obtain.
Wei-Qiang Zhang
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Iris feature extraction through wavelet mel-frequency cepstrum coefficients
Optics and Laser Technology, 2019Abstract In this paper, a novel technique based on wavelet cepstrum feature is discussed for iris recognition system. The proposed method is based on the wavelet derived from the popular biorthogonal Cohen-Daubechies-Feauveau 9/7 filter bank. Moreover, being biorthogonal in nature it has superior frequency selectivity, symmetric, and better time ...
Arun Kumar Sangaiah +2 more
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Optical Fiber Intrusion Signal Recognition Based on Improved Mel Frequency Cepstrum Coefficient
2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2018Oil and gas resources pipelines, boundary lines and other places need to monitor their safety status in real time. The fiber early warning system becomes a good choice for its high sensitivity, corrosion resistance and concealment. The system provides early warning of the detection of fiber vibration signals.
Qing Tian
exaly +3 more sources
Speaker verification using mel-frequency cepstrum coefficient and linear prediction coding
2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE), 2017Identity verification is one of the most important concern in today's era of information technology. Conventionally, it is done using keys or password which could be stolen and are not suitable for critical purposes. To overcome these problem various biometric verification system have emerged, such as iris recognition, figure print recognition and ...
Shubhangi Agrawal, D.K. Mishra
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The 2010 International Joint Conference on Neural Networks (IJCNN), 2010
We present a non-destructive watermelon classification method using Mel-Frequency Cepstrum Coefficients (MFCC) and Multi-Layer Perceptron (MLP) neural network. Acoustic signals were collected from thumping noises of ripe and unripe watermelon fruits. MFCC was then used to convert the signals into MFCC coefficients.
Azlee Zabidi, Ihsan M Yassin
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We present a non-destructive watermelon classification method using Mel-Frequency Cepstrum Coefficients (MFCC) and Multi-Layer Perceptron (MLP) neural network. Acoustic signals were collected from thumping noises of ripe and unripe watermelon fruits. MFCC was then used to convert the signals into MFCC coefficients.
Azlee Zabidi, Ihsan M Yassin
exaly +3 more sources
2015 International Conference on Intelligent Transportation, Big Data and Smart City, 2015
Characteristic extraction is one of the main progresses of identification and features of this extraction must reflect not only the nature of targets but also the differences between them, in order to help the recognition unit to make classifying recognition. In this article, we study and research the characteristics of a variety of ship radiated noise
Mu Lin +4 more
exaly +2 more sources
Characteristic extraction is one of the main progresses of identification and features of this extraction must reflect not only the nature of targets but also the differences between them, in order to help the recognition unit to make classifying recognition. In this article, we study and research the characteristics of a variety of ship radiated noise
Mu Lin +4 more
exaly +2 more sources
Compensated mel frequency cepstrum coefficients
1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002The high concentration of energy in the low frequency range observed for most speech spectra is considered a nuisance because it makes less relevant the energy of the signal at middle and high frequencies in many speech analysis algorithms. This problem is often partially solved by filtering the input signal with a single-zero high pass filter.
Rivarol Vergin +2 more
openaire +2 more sources