Convolution Neural Network Model to Classify Photo Gallery on an Android Device

V. Krishna Mohan; N. Aarthi Sai; S. Arun Kumar; A. Sathwika

International Journal of Analog Integrated Circuits

Convolution Neural Network Model to Classify Photo Gallery on an Android Device

Abstract

The classification of images is a classic topic in the domains of image processing, computer vision, and machine learning. Convolution Neural Networks, a sort of deep learning that falls under the Machine Learning sub-domain, have been used in this model. This model was inspired by the problem that students experience at the end of the academic year is that their phones become cluttered with photos from various sources. The aim of this paper is to build a model that separates the photographs into required categories with 98% accuracy. This model takes the folder location as input and evaluates each image before categorizing them into three classes namely Hand written, Text and Personal pictures. As a result, it is simple for the user to free up memory or use for future references in mobile devices like smartphones, tablets and laptops. This method incorporates the MobileNetV2 framework with a fully convolutional developed on real-time data in a GPU scenario.

Full text

The full text of this article is available to subscribers.

On a subscribing campus you are let in by network address, with no login at all.

One-off purchase. Permanent access to this article, no account needed.

A year of online access to every article in International Journal of Analog Integrated Circuits. Or choose several journals →

How to cite

V. Krishna Mohan, N. Aarthi Sai, S. Arun Kumar, A. Sathwika. Convolution Neural Network Model to Classify Photo Gallery on an Android Device. International Journal of Analog Integrated Circuits. 2023;8(1):9–17.

Download the citation:

Article details

Convolution Neural Network Model to Classify Photo Gallery on an Android Device

Abstract

Read more of it

Publish your article

Abstract

Related articles

Electric Vehicle Integration to Stabilize the Grid by Improving Power Quality

Operational-Amplifier-Based Realization of a 1-BitArithmetic Logic Unit: Design, Implementation, and Experimental Validation

An Extensive Analysis of QC's Difficulties & Restrictions

Smart Battery Management System with Real-Time Estimation of SOC and SOH

A Overview on Reimagining MOSFET as Precision Thermal Sensor

Phase-Change Material Integrated Semiconductor Circuits for In-Memory Analog Computing Applications

Read more of it

Publish your article