Numerous high-accuracy neural networks for object detection have been proposed in recent years. Creating a specific training dataset seems to be the main obstacle in putting them into practice. This paper aims to overcome this obstacle and proposes an automatic dataset creation method. This method first extracts objects from the source images and then combines them as synthetic images. These synthetic images are annotated automatically using the data flow in the process and can be used directly for training. To the best of our knowledge, this is the first automatic dataset creation method for object detection tasks. In addition, the adaptive object extraction method and created natural synthetic images make the proposed method maintain strong adaptation and generalization ability. To validate the feasibility, a dataset that includes 44 categories of objects is created for the object detection task in a vending supermarket. Under the strictest metric $AP_{75} $ , both the trained EfficientDet and YOLOv4 achieve higher than 95% in accuracy on the common difficulty testing set and higher than 90% in accuracy on the high difficulty testing set.

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A Method to Automatic Create Dataset for Training Object Detection Neural Networks

Person re-identification aims at automatically retrieving a person of interest across multiple non-overlapping camera views. Because of increasing demand for real-world applications in intelligent video surveillance, person re-identification has become an important computer vision task and achieved high performance in recent years. However, the traditional person re-identification research mainly focus on matching cropped pedestrian images between queries and candidates on commonly used datasets and divided into two steps: pedestrian detection and person re-identification, there is still a big gap with practical applications. Under the premise of model optimization, based on the existing object detection and person re-identification, this paper achieves a one-step search of the specific pedestrians in the whole images or video sequences in the real scene. The experimental results show that our method is effective in commonly used datasets and has achieved good results in real-world applications, such as finding criminals, cross-camera person tracking, and activity analysis.

Person re-identification in the real scene based on the deep learning

In order to solve the problems of complex cabling,hard maintenance and high cost in wired temperature and humidity acquisition system available,a design scheme of wireless temperature and humidity acquisition system based on Z-Stack is proposed.This system with the adoption of CC2430 radio chips and SHT11 digital temperature and humidity sensor is developed based on Zigbee protocol stack.The principle of the system and hardware design and software design of node are introduced.The experimental results show that the system can achieve the temperature and humidity data collection stably and reliably.

Wireless temperature and humidity acquisition system based on Z-Stack

The companionship of pets can help the owner's mental health to a large extent, reduce the stress of the owner, and give the owner a sense of security and need. However, the tension of the pace of life sometimes makes the owner ignore the improvement of the pet's living environment, which is not conducive to the health of the pet. Therefore, the monitoring and control of the temperature and humidity of the pet living environment and the light environment is very important. In this design, the high reliability of the more comprehensive research is adopted, and the microcontroller processor STC89C52 is the core, which improves the temperature and humidity of the pet environment Implement functions for sub-function design. The main functions of the design include temperature and humidity acquisition, display and automatic control adjustment. For the selection of equipment, with the goal of operational stability and cost performance, the corresponding equipment is selected, and finally the temperature and humidity adjustment is realized. At the same time, for the corresponding software process, the molecular programming and the main program synthesis are adopted to finally ensure that the pet temperature and humidity and control system functions can be realized and the system can operate perfectly. The system devices designed in this paper are cost-effective, have clear circuit structures and have strong operational stability. The design of this article can be widely used in family life to benefit the living environment of pets.

Design of Pet temperature and humidity control system based on microcontroller

Based on the Z-Stack protocol Stack, with the CC2530 radio frequency transceiver chip and DHT22 digital temperature and humidity sensor as the core, this article puts forward a new implementation designed for the wireless temperature and humidity acquisition system on the basis of the Zigbee wireless communication technology. With the method of upper machine software by GUI, changes in temperature and humidity can be shown on the display terminal intuitively. The article mainly expounds the system structure design, temperature andhumiditydataacquisitionprocessandgraphicalinterfacemonitoringimplementation. Experimentsshowthat the wireless sensor system can make the real-time data acquisition of temperature and humidity, which has not only good eﬃciency and scalability, but also high reliability and excellent stability.

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Design of Wireless Temperature and Humidity Acquisition System

Person Re-identification as an important supplement to face recognition, refers to a network of cameras with non-overlapping vision domains, through the use of computer vision technology to solve the cross-camera and cross-scene pedestrian recognition and retrieval. That is, determine whether there is a specific pedestrian to be detected in the different images or different video sequences. At present, many person re-identification research works mainly carried out through experimental verification and evaluation on large ReID datasets such as Market-1501, DukeMTMC-reID, MSMT17, and CUHK03. In this paper, based on the existing deep-learning person re-identification research, combines with the actual application scenarios, under the premise of analyzing the technical feasibility, we propose a complete process for Person Re-identification based on mobile devices, aims to combine pedestrian detection and person re-identification to perform real-time pedestrian detection and query. In this process, not only the features extracted by pedestrians can be reused, but also the research on person re-identification can be better and effectively applied, such as tracking criminals and searching for missing children.

/pdf/person-re-identification-on-mobile-devices-based-on-deep-ribtefqivs.pdf

Person Re-identification on Mobile Devices Based on Deep Learning

Based on the Z-Stack protocol Stack, with the CC2530 radio frequency transceiver chip and DHT22 digital temperature and humidity sensor as the core, this article puts forward a new implementation designed for the wireless temperature and humidity acquisition system on the basis of the Zigbee wireless communication technology. With the method of upper machine software by GUI, changes in temperature and humidity can be shown on the display terminal intuitively. The article mainly expounds the system structure design, temperature and humidity data acquisition process and graphical interface monitoring implementation. Experiments show that the wireless sensor system can make the real-time data acquisition of temperature and humidity, which has not only good efficiency and scalability, but also high reliability and excellent stability.

/pdf/wireless-temperature-and-humidity-acquisition-system-based-3sesy72pdp.pdf

Zhenjiang Qian

Papers

Design of Wireless Temperature and Humidity Acquisition System

Person Re-identification on Mobile Devices Based on Deep Learning

Person re-identification in the real scene based on the deep learning

Wireless Temperature and Humidity Acquisition System Based on Z-Stack Protocol Stack