Krawtchouk Moment Based Interactive Image Retrieval Algorithm

Raghuraman, G.; Ananth, J. P.; Shunmuganathan, K. L.; SaiRamesh, L.

doi:10.1166/jctn.2015.4684

Cited by 5 publications

(1 citation statement)

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“…In [6], authors implements region of interest to enhance the segmentation and retrieval process which is extended the process using K-means clustering algorithm for grouping the same kind of image [7]. Another work in [8] discussed about the image retrieval process using krawtchouk method. But in recent times deep learning methods are used to enhance retrieval efficiency in image processing [9][10].…”

Section: Literature Surveymentioning

confidence: 99%

Smart Household Object Detection Using CNN

Vatchala

Sasidevi

Dhanalakshmi³

et al. 2022

Advances in Parallel Computing Algorithms, Tools and Paradigms

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Object detection is one of the most basic and central tasks in computer vision. object detection is a subset of object recognition. Its task is to find all the interested objects in the image, and determine the category and location of the objects. Object detection is widely used and has strong practical value and research prospects. Applications include face detection, pedestrian detection and vehicle detection. In recent years, with the development of convolutional neural network, significant breakthroughs have been made in object detection. This work aim to detect objects in the video frames. It detects household objects and predicts the object where it may be present. Convolutional Neural Networks (CNN) is used to detect objects in the environment. Then Resnet50 is used to classify the images into objects. Then Support vector machine (SVM) is used to train objects and stored in object database. It will be retrieved whenever neural networks sent object for verification.

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Section: Literature Surveymentioning

confidence: 99%