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Enhance Egocentric Grasp Recognition Based flex sensor Under Low Illumination

Computers, Materials & Continua 2022年第6期71卷 4377-4389页

作者： Chana Chansri Jakkree Srinonchat Faculty of Engineering Rajamangala University of Technology ThanyaburiPathum Thani12110Thailand

Egocentric recognition is exciting computer vision research by acquiring images and video from the first-person ***,an image becomes noisy and dark under low illumination conditions,making subsequent hand detection tasks ***,image enhancement is necessary to make buried detail more *** article addresses the challenge of egocentric hand grasp recognition in low light conditions by utilizing the flex sensor and image enhancement algorithm based on adaptive gamma correction with weighting ***,a flex sensor is installed to the thumb for object *** thumb placement that holds in a different position on the object of each grasp affects the voltage changing of the flex sensor *** average voltages are used to configure the weighting parameter to improve images in the image enhancement ***,the contrast and gamma function are used to adjust varies the low light *** grasp images are then separated to be training and testing with pretrained deep neural networks as the feature extractor in YOLOv2 detection network for the grasp recognition *** proposed of using a flex sensor significantly improves the grasp recognition rate in low light conditions.

关键词： Egocentric vision hand grasp flex sensor low light enhancement

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Intelligent sowing depth regulation system based on flex sensor and Mamdani fuzzy model for a no-till planter

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International Journal of Agricultural and Biological Engineering 2021年第6期14卷 145-152页

作者： Mingwei Li Xiaomeng Xia Longtu Zhu Renyi Zhou Dongyan Huang School of Biological and Agricultural Engineering Jilin UniversityChangchun 130022China Key Laboratory of Bionic Engineering Ministry of EducationJilin UniversityChangchun 130022China

Sowing depth has an important impact on the performance of no-tillage planters,it is one of the key factors to ensure rapid ***,the consistency of sowing depth is easily affected by the complex environment of no-tillage *** order to improve the performance of no-tillage planters and improve the control precision of sowing depth,an intelligent depth regulation system was *** flex sensors installed on the inner surface of the gauge wheel at 120°intervals were used to monitor the downward force exerted by the seeding row unit against *** peak value of the output voltage of the sensor increased linearly with the increase of the downward *** addition,the pneumatic spring was used as a downforce generator,and its intelligent regulation model was established by the Mamdani fuzzy algorithm,which can realize the control of the downward force exerted by the seeding row unit against ground and ensure the proper seeding *** working process was simulated based on MATLAB-Simulink,and the results showed that the Mamdani fuzzy model performed well in changing the pressure against *** results showed that when the operating speed was 6 km/h,8 km/h and 10 km/h,the error of the system’s control of sowing depth was±9 mm,±12 mm,and±22 mm,respectively,and its sowing performance was significantly higher than that of the unadjusted passive operation.

关键词： flex sensor Mamdani fuzzy model sowing depth intelligent regulation system no-till planter

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A New Intelligent Approach for Deaf/Dumb People based on Deep Learning

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Computers, Materials & Continua 2022年第9期72卷 6045-6060页

作者： Haitham Elwahsh Ahmed Elkhouly Emad Abouel Nasr Ali K.Kamrani Engy El-shafeiy Computer Science Department Faculty of Computers and InformationKafrelsheikh UniversityKafrelsheikhEgypt Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh 11421Saudi Arabia Industrial Engineering Department College of EngineeringUniversity of HoustonHoustonTX 77204-4008USA Department of Computer Science Faculty of Computers and Artificial IntelligenceUniversity of Sadat CitySadat CityEgypt

People who are deaf or have difficulty speaking use sign language,which consists of hand gestures with particular motions that symbolize the“language”they are communicating.A gesture in a sign language is a particular movement of the hands with a specific shape from the fingers and whole *** this paper,we present an Intelligent for Deaf/Dumb People approach in real time based on Deep Learning using Gloves(IDLG).The approach IDLG offers scientific contributions based deep-learning,a multimode command techniques,real-time,and effective use,and high accuracy *** this purpose,smart gloves working in real time were *** data obtained from the gloves was processed using deep-learning-based approaches and classified multi-mode commands that allow dumb people to speak with regular people via their smart ***,the glove has five flex sensors and an accelerometer using to achieve Low-Cost Control *** flex sensor generates a proportional change in resistance for each individual *** processing of these hand gestures is in Atmega32A Microcontroller which is an advance version of the microcontroller and the lab view *** compares the input signal to memory-stored specified voltage *** performance of the IDLG approach was verified on a dataset created using different hand gestures from 20 different *** the test using the IDLG approach on 10,000 data points,process time performance of milliseconds was achieved with 97%accuracy.

关键词： Deep learning flex sensor labview Atmega32A low-cost control system accelerometer intelligent glove

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Monitoring the Turmeric Finger Disease and Growth Characteristics Using sensor Based Embedded System —A Novel Method

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Circuits and Systems 2016年第8期7卷 1280-1296页

作者： Maheswaran Shanmugam Asokan Ramasamy Sivaranjani Paramasivam Priyadharshini Prabhakaran Department of ECE Kongu Engineering College Erode India Kongu Nadu College of Engineering and Technology Trichy India

In this cyber era, novelty plays a prime role in the field of agriculture that majorly depends on computer-based measurements and control. Herein before, it was totally controlled and performed by the agriculturists. One of the technological innovative methods to measure and monitor the turmeric finger growth characteristics is the embedded system that is based on sensor array module such as flex sensor, temperature sensor and pH sensor. The experimental work has been designed and tested with five set of nodes and the growth of turmeric finger is tenuously monitored by measuring the change in flex resistance. Out of five nodes, two nodes were diseased. Deliberately, one node was left as such and the other node was treated with natural pesticides (pseudomonas and viride) to restrict the rhizome rot disease attack. After cultivation, it was found that the rhizome rot disease attack on the node which was treated with pesticides was comparatively lesser than the other node. The five different nodes have been used in the experimental work with an average flex sensor resistance of 3.962 cm/kΩ. In a nutshell, this proposed method manifests the farmers to detect the rhizome rot disease at its earlier stage and to prevent it as well by screening the growth of the turmeric fingers when it is under the soil.

关键词： Embedded System Turmeric Finger Growth Rhizome Rot Disease Natural Pesticides flex sensor

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