Pedestrian detection using Doppler radar and LSTM neural network

Azizi, Mussyazwann Azizi Mustafa; Noh, Mohammad Nazrin Mohd; Pasya, Idnin; Yassin, Ahmad Ihsan Mohd; Ali, Megat Syahirul Amin Megat

doi:10.11591/ijai.v9.i3.pp394-401

Cited by 4 publications

(4 citation statements)

References 22 publications

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“…The usual simplified circuit for reading signals with a constant voltage, which was used in the experiments, is shown in Figure 1. In the future, regardless of the purpose of the HRG or as an angle sensor [22], or an angular velocity sensor, and regardless of the algorithm for further signal processing in the digital part of the equipment, the magnitude of the resonator oscillations is measured at the location of the signal pickup electrodes. Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Method for measuring voltages in channels of a hemispherical resonator gyroscope with an arbitrary orientation axes

Parkhomey

Boiko²,

Zeniv³

et al. 2023

IJEECS

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The article deals with issues related to solid wave gyroscopes, which are used as a sensor in inertial navigation systems. The article considers a variant of solving problem, when oscillations of the resonator are excited in directions that coincide with their own axes, oriented a priori is unknown. The main contribution this article is the method is proposed for measuring signal amplitudes in virtual main and quadrature channels, the orientation of which does not coincide with the orientation of the signal pickup electrodes. This is achieved by modeling algorithms for measuring the slope of the resonator's own axes and signal amplitudes in virtual channels are evaluation. In order to verify the adequacy of the proposed models simplified calculation formulas for programming microcontrollers are presented. An estimate of the error due to the use of simplified formulas is made. It is assumed that the use of this method will reduce the requirements for the quality of balancing the resonators of gyroscopes. The findings will be useful for mass production of navigation systems with gyroscopes, which have a small drift and are capable of experiencing large shock linear accelerations, for example, in underground inclined drilling, and in meteorological rockets.

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Section: Introductionmentioning

confidence: 99%

Method for measuring voltages in channels of a hemispherical resonator gyroscope with an arbitrary orientation axes

Parkhomey

Boiko²,

Zeniv³

et al. 2023

IJEECS

View full text Add to dashboard Cite

show abstract

“…The method can generally be segregated based on the type of data being used. While the long short-term memory (LSTM) network specifically caters for time-series information [10], convolutional neural network (CNN) is developed for image recognition [11].…”

Section: Introductionmentioning

confidence: 99%

Classification of nutrient deficiency in oil palms from leaf images using convolutional neural network

Razali

Hairuddin

Jahidin

et al. 2022

IJ-AI

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Oil palm is a perennial plant that thrives well in tropical climate. Apart from humid environment, the plant also requires a wide variety of nutrients. Any deficiencies will directly affect its growth and palm oil production. These can often be detected from the change of leaf colour and texture. Deviations from the standard dark green colour indicates lack of certain nutrients. Therefore, this study proposes convolutional neural network (CNN) to classify nutrient deficiency in oil palms using leaf images. A total of 180 leaf images are acquired using standardized protocol. The samples are evenly distributed into healthy, nitrogen-deficient, and potassium-deficient groups. Residual network (ResNet)-50, visual geometry group-16 (VGG16), Densely connected network (DenseNet)-201, and AlexNet are trained and tested using the randomized samples. Each attained classification accuracies of 96.7%, 100%, 98.3%, and 100% respectively. Despite yielding similar performance, AlexNet is the more computational efficient architecture with less convolutional layers compared to VGG-16.

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“…Without an adequate amount of corpus, it cannot achieve better translations. NMT uses RNN architecture [4] and mainly depends on the parallel corpus. So, there is a need to collect more parallel corpus for better translations.…”

Section: Introductionmentioning

confidence: 99%

Effective preprocessing based neural machine translation for English to Telugu cross-language information retrieval

Raju

Satyanarayana

2021

IJ-AI

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In cross-language information retrieval (CLIR), the neural machine translation (NMT) plays a vital role. CLIR retrieves the information written in a language which is different from the user's query language. In CLIR, the main concern is to translate the user query from the source language to the target language. NMT is useful for translating the data from one language to another. NMT has better accuracy for different languages like English to German and so-on. In this paper, NMT has applied for translating English to Indian languages, especially for Telugu. Besides NMT, an effort is also made to improve accuracy by applying effective preprocessing mechanism. The role of effective preprocessing in improving accuracy will be less but countable. Machine translation (MT) is a data-driven approach where parallel corpus will act as input in MT. NMT requires a massive amount of parallel corpus for performing the translation. Building an English - Telugu parallel corpus is costly because they are resource-poor languages. Different mechanisms are available for preparing the parallel corpus. The major issue in preparing parallel corpus is data replication that is handled during preprocessing. The other issue in machine translation is the out-of-vocabulary (OOV) problem. Earlier dictionaries are used to handle OOV problems. To overcome this problem the rare words are segmented into sequences of subwords during preprocessing. The parameters like accuracy, perplexity, cross-entropy and BLEU scores shows better translation quality for NMT with effective preprocessing.

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Pedestrian detection using Doppler radar and LSTM neural network

Cited by 4 publications

References 22 publications

Method for measuring voltages in channels of a hemispherical resonator gyroscope with an arbitrary orientation axes

Method for measuring voltages in channels of a hemispherical resonator gyroscope with an arbitrary orientation axes

Classification of nutrient deficiency in oil palms from leaf images using convolutional neural network

Effective preprocessing based neural machine translation for English to Telugu cross-language information retrieval

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