recognition rate

Experiment results demonstrate that this algorithm is better than KL transform in the computational speed and the recognition rate.

The simulation results show that the average fusion recognition rate of the proposed scheme outperforms that of decision templates.

The experiment results suggest that this method solves the drawback of preprocessing in a large extent and achieves high recognition rate.

The experimental results show the algorithm is simple and easy-to-implement, and is satisfactory in execution time and recognition rate.

For the influence of environment and hardware, the recognition rate of color is usually not good for robots.

Comparative experimental result shows that this algorithm keeps a high recognition rate when improving the arithmetic efficiency.

Music disturbance reduces recognition rate of the word command in the car word command recognition system.

Changing illumination condition can change the result of image segmentation algorithm and reduce the intelligent recognition rate.

Experimental results show that the system to improve recognition rate, effectively solve the problems of simple voice analysis.

The recognition rate of voice-recognition system has reached a very high standard, especially in a quiet environment.

The results show that the image recognition rate is up to 100% for road navigation with the proposed method.

Simulation results showed that this algorithm can recognize CW, FSK and PSK signal and it is robust and has good recognition rate.

In practice, the recognition rate of horizontal number is up to 98%, the recognition rate of vertical number is up to 93%.

Experimental results show that the proposed algorithm has a high recognition rate and a good perspective.

SVM kernel function is one of the most critical factors that affect the recognition rate.

Experimental results show that the method can effectively improve the recognition rate of face recognition systems.

The key technology improves the system recognition rate is the SVM kernel function and parameter optimization.

However, the recognition rate will decline sharply due to the shape and texture change in the face for different age.

Experiments on 806 real life courtesy amount images demonstrate the efficient of this algorithm, and the recognition rate is up to 91. 4%.

Experiment results show that the method is an effective data fusion method which can access higher recognition rate.

The experiment shows that the model can achieve high recognition rate and is suitable for complex ear image libraries.

Aim of the proposed methods is reducing or eliminating the statistical correlation between features and improving recognition rate.

The simulation results show that this method improves the image recognition rate to 91. 2%.

Experiments are performed on the NIST database to acquire the comparison of the searching efficiency and generalized recognition rate.

The experiment result of recognition rate is about 98% which has a better performance than distance classification and neural network.

The experimental results show that the algorithm is fast and anti-noise strong, effectively improve the speed and barcode recognition rate.

The experimental results show that SVM method has higher recognition rate of urine sediment classification.

The results show that it has high computation speed and higher recognition rate.

The advantage of the algorithm is short time training, high recognition rate and short time detection.

Experimental results show that the algorithm has good noise immunity, improved two-dimensional bar code recognition rate.

Additionally, those symbols with low recognition rate should be introduced to public through education.

Experiment shows that the recognition rate of the proposed method is about 90% and it is an effective face recognition method.

The invention relates to a method for improving speech recognition rate with gain self-adapting.

The fault recognition method proposed in this paper features higher recognition rate than artificial neutral network method.

The experiments show using fuzzy support vector machine significantly improves the overall recognition rate.

It holds the advantages of high correct recognition rate, strong anti-noise ability, rapid recognition speed, and high security.

Accurately registering iris images leads tohigher recognition rate for an iris recognition system.

The experimental results show that the correct recognition rate of the proposed method can reach 99. 976% without noise mask.

The individual character recognition rate of this system is over 96% and the whole license plate recognition rate is 82%.

The multi-sensors fusion based hand gesture recognition improved the recognition rate which gives out better results.

The experimental results show that the performance of FDBNN is better than that of BP and DBNN on stability and recognition rate.

In this paper, phoneme duration information is added to the conventional model to improve the recognition rate.

If builds the movie studio average recognition rate to be possible to enhance about 10%.

Experimental results show that using SVM-GMM model can improve the open-set speaker recognition rate effectively.

Thus we used Touchless Fingerprint Sensor to avoid possibility that the dust could affect the recognition rate.

We have used sample images to test the face recognition application based the methods above, and the recognition rate is above 85%.

Feature extraction method of face image, which boasts simplicity and high recognition rate, is proposed.

The algorithm is simple and reliable, asking with less original data signal but higher recognition rate.

Experiments show that the new MDV is stabile and distinct, the algorithm with high recognition rate is very quick, and almost real time.

Experiments show that the initiative to improve the shape model in shape recognition rate has been steady.

The cross validation method with leave-one-out was used to estimate the recognition rate, and the accuracy was 94. 44%.

In order to verify the parameters are or not effect on recognition rate of system, the second study was performed by ANOVA tests.

Experimental results confirm that the method has a high recognition rate of greater than 90%.

Experiments have proved that the matching method based on BP neural network achieved good results on both speed and recognition rate.

As the recognition rate is relatively high, the ratio of correct and wrong the number of samples has reached 8: 1.

The experimental results show that the depended speaker speech recognition rate is 98%.

And now many mature systems have got fairly high speech recognition rate in laboratory.

The result indicated: the method has a higher recognition rate than the traditional LDA and PCA in the lower dimension space.

In the first (January) survey, the average recognition rate for the top five members was 74%, and the average support rate was 57 points.

Our system run well, and the recognition rate initially achieves the practical level.

This paper sets up a new Support Vector Machine-Gussian Mixture Model(SVM-GMM) to improve speaker recognition rate based on open-set.

In order to acquire a high recognition rate, the textural information of iris images must be extracted effectively.

Because of the similar global features of different typefaces , the method also has high recognition rate.

According to the experimental result, our recognition rate of OMR system is 82%.

In the SVM-based speaker recognition system study, it is important to obtain a ideal recognition rate.

Elastic matching has relatively higher recognition rate but also higher calculation complexity, which limits its application.

In some cases, rogue brands boast a higher sponsor-recognition rate than the firms that foot the bills.

The result shows that the system not only can detect the defects effectively but also can reach a character recognition rate of 95%.

This method reduces the computation time and improves the recognition rate.

Experimental results show that the modified algorithm can achieve recognition rate of 94. 4% based on 320 ear images in database.

From the experimental results, we have 50 studying samples and 47 testing samples in the first stage, the recognition rate is 100%.

The algorithm has the characteristic of high recognition rate, good extension and so on.

By using the C4. 5 and the support vector machine, the improved algorithm proposed in this paper achieved a higher recognition rate.

The bubble recognition rate is higher than 95%, so it can meet the practical need of industry detection.

Experiments show that our Touchless Fingerprint Recognition System can reach recognition rate from 71. 43% to 92. 86%.

For 40 studying samples and 39 testing samples in the second stage, the recognition rate is 100%.

SVC not only has a high time complexity but also gets low recognition rate when distribution of the data set is complex and uneven.

Therefore, in order to improve the recognition rate, we must find new ways and means.

But recognition rate is still low because of the influence of the noise in nature environment. It can not be used in actual occasion.

The teat result shows the recognition rate by using multi-feature fusion is much higher than that by using single feature.

The RBF neural networks were trained with the data of 10 kinds of pesticides and other gases. The correct recognition rate reaches 83. 3%.

Influence of Two Improved Types of LPC Characteristic Parameters on Recognition Rate

Improving the recognition rate of speech for dialogue system using expectation

Feature Selection Based on Simulated Annealing Algorithm and the Recognition Rate of the Nearest Neighbor Classifier

Experimental Research on Audio Visual Fusion and on Model Asynchrony for Raising Speech Recognition Rate

results show that ann has a higher recognition rate and potential advantages in automatic speech recognition

Research on the Correlation of Speech Recognition Rate and Retrieval Performance

establishing codebook using only one word to improve the recognition rate;

Improving the Recognition Rate of EEG in BCI Based on Genetic Algorithm and Probabilistic Neural Network

for accuracy, this method can recognize and locate the mature fruit in images, the correct recognition rate reaches to 93. 3%;

but gait recognition rate is relatively low

the recognition rate is about 75 %

according to the test , the recognition rate is above 95 %

many kinds of ocr technology has gotten very high recognition rate