Object recognition in images using convolutional neural network

Sudharshan, Duth P.; Raj, Swathi

doi:10.1109/icisc.2018.8398912

Cited by 14 publications

(2 citation statements)

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“…The reviews work that has utilized digital image processing techniques to automate the identification of plant species by their leaf shapes. Image recognitions dependent on leaf images have a fixed structure framework [20]. A special gadget gains the object image (e.g., a camera).…”

Section: Leaf Identification Systemmentioning

confidence: 99%

Android Application of Leaf Identification System

Minhat

Saon

Mahamad

et al. 2022

Int. J. Interact. Mob. Technol.

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Leaf identification image is consistently a difficult task when using computer vision. The convolutional component extraction methods on images have their impediment and limitation, such as low accuracy, are not adaptable and less promising when converted to genuine application. The reasons are the lack of dataset needed to build a recognition model. Likewise, using the computer as a tool is bothering as it restricts the task in the research lab only. Convolutional Neural Network (CNN) shows a great solution for the computer version. Subsequently, this project utilizes the CNN’s properties to solve the image classification task, and the CNN model chosen is run in Phyton coding in TensorFlow Lite. It is similar to TensorFlow’s running code, but this project focused on building an Android application. It can perform faster and produce high accuracy results. There are four types of leaves involved in this project: betik, kari, pudina, and cengal. As a result, the model could reach around 99% accuracy with a 0.176 error rate. Ultimately, an Android application called Leaf identification is created. The model is sent and integrated into the apps that work with a concentrated information base to help put away and deal with the pictures. Hence, an Android leaf image identifier using CNN is proposed to solve the stated problem and is believed to contribute to education and research.

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Section: Leaf Identification Systemmentioning

confidence: 99%

Android Application of Leaf Identification System

Minhat

Saon

Mahamad

et al. 2022

Int. J. Interact. Mob. Technol.

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“…The object detection algorithm is also used to find images online similar to the image given input to the model [9]. In other words, it enables search by image.…”

mentioning

confidence: 99%

Various object detection algorithms and their comparison

Mishra

Rout

Mishra

et al. 2022

IJEECS

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This paper presents a detailed and comparative analysis of various object detection algorithms. The challenge of object detection is taken care of while studying various algorithms. Throughout the year various methods have been discovered in this field, each having its advantages and drawbacks. This paper aims at providing the systematic study of all the popular algorithms including the conventional ones. Although many methods and techniques come up each year and each of them having superiority other the previous models but at the same time even complexity increases. In this paper, some famous and basic methods of object detection and tracking are discussed. Using these developed techniques good results can be obtained and also the comparison of the efficiency of all the models can be done. Real-time applications and the outcomes are also discussed.

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