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Optimizing Object Detection in Bio-Waste Management with Improved Hyperbolic Tangent YOLOv5 and Binarization-Adapted K-Means Algorithm

by

Murugesan Shanmugavelu et al. View all

Issue 10

Biowaste

With the increasing importance of green development, bio-waste classification has become an important element of green development. However, in garbage stacking scenarios, the task of segmenting highly overlapping objects is difficult because the bottom garbage is in an occluded state and it is...

Garbage Object Detection Machine Learning +4 more
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Efficient Biomedical Waste Management: Optimizing Segmentation and Classification with EnU-Net-DNN-BMWC

by R.S. G. Konel K. Madeshwaren V.

Issue 10

Solid Waste Management

In India, biomedical waste (BMW) management is governed by strict regulations to mitigate health and environmental risks. It includes materials such as sharps, infectious wastes, pharmaceuticals, and non-hazardous items contaminated with potentially infectious substances. Proper management and...

Biomedical waste Deep learning +2 more
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Air Pollution Monitoring Model in Real-time with cloud based Channel Ranging and Stego Privacy Preservation

by Radhakrishnan C. Asokan R.

Issue 6

Air Quality

Monitoring air quality in polluted environments is crucial for human health, but traditional methods using meteorological equipment have limitations in complex terrains and are costly. This study proposes a novel approach to address air pollution monitoring in urban areas by visually assessing the...

Air quality monitoring Urban Pollution +3 more
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A Deep Learning-Based Buffalo Optimizer based Squeeze and Excitation Network for Garbage Classification for a Sustainable Environment

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Subhashini R et al. View all

Issue 3

Solid Waste Management

A Squeeze and Excitation Network is a deep-learning architectural component designed to enhance networks. The "squeeze" step reduces the spatial dimensions of the input feature maps, and the "excitation" step adaptively recalibrates channel-wise feature responses. This allows the network to focus on...

Smart garbage management Deep learning +2 more
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Integrated Disaster Risk Management for Flood Detection on Remote Sensing Images using Deep Learning techniques

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Arun Mozhi Selvi Sundarapandi et al. View all

Issue 9

Floods, Droughts and Water scarcity

Floods are one of the leading causes of damage, prompting mortality and substantial destruction to the structure and total economy of the affected nations. Remote sensing, satellite imagery, global positioning system, and geographic information system (GIS) are widely employed for flood...

Remote Sensing disaster risk management +2 more
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Assessment of Object-Based Classification for Mapping Land Use and Land Cover using Google Earth

by

Dr. Geraldine Bessie Amali D et al. View all

Issue 7

Environmental data analysis and modelling

Land Use and Land Cover (LULC) maps perform a significant part in Remote Sensing (RS) in monitoring and analyzing earth information for human development. Because of the high spectrum variability, LULC classification from RS data is extremely difficult. The study's objective is to assess the object...

Remote Sensing Land Use and Land Cover +3 more
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Artificial Intelligence with Earthworm Optimization Assisted Waste Management System for Smart Cities

by

J. Rajalakshmi et al. View all

Issue 4

Solid Waste Management

In recent days, massive quantity of waste materials gets considerable increased with increasing population. Proper management of waste materials becomes essential to reduce environmental degradation and improve quality of life in smart cities. Waste management helps to collect and treat waste...

Computer vision Smart city +6 more
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Deep Learning Driven Crop Classification and Chlorophyll Content Estimation for the Nexus Food higher Productions using Multi-spectral Remote Sensing Images

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G.Chamundeeswari et al. View all

Issue 3

Water, Energy and/or Food Nexus

Due to the development of open access medium-high resolution remote sensing data like multispectral remote sensing images, crop classification becomes a hot research topic to be realized on large scale using machine learning (ML) models. At the same time, chlorophyll content is a critical index used...

Multispectral remote sensing images Agriculture +4 more
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Estimation of changes in the Dead Sea surface water area through multiple water indices and geospatial techniques

by

Majed Mahmoud Ibrahim et al. View all

Issue 4

Water Resources Management

The study calculated the changes in the Dead Sea surface area from 1984 to 2019. The satellite images of 1985, 1990, 2000, 2010, and 2019 were classified by applying four different methods to estimate the changes in the Dead Sea surface water area. The methods included normalized difference water...

Water indices GIS +3 more
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Evaluation of the effect of land use change on runoff using supervised classified satellite data

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Reza Ghazavi et al. View all

Issue 2

Water Resources Management

The main objective of this study was to determine the effect of land use change on runoff in Chenar Rahdar watershed. Land use map of the studied basin was determined using Landsat satellite imagery for 2004 and 2015 using ENVI software. After applying the necessary corrections to the images and...

land use Rain Runoff +2 more
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Landcover change modeling through visualization and classification enhancement of multi-temporal imagery

by

Panagiotis Partsinevelos et al. View all

Issue 2

General

The natural environment endures natural and human-induced changes. Remote sensing has been providing monitoring oriented solutions by a series of methodologies which contribute to prudent environmental management. Analysis of multi-temporal satellite images for the observation of the land changes...

classification land use/land change +2 more
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