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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Empowering Water Treatment Through Convolutional Neural Network Classification |
| Authors Name: | Chowdam Vinaya Sri , Ayushmann Arya Kumar , Suman kumar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_219374
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| Published Paper Id: | IJNRD2404747 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | With significant development of Internet of Things and substantial advancements in sensors, researchers can now readily obtain photos of the water and use them to understand what is happening in the ecosystem. In essence, expanding data size and category helps address issues related to water contamination. In this research, we concentrate on categorizing water photos into subcategories of clean and contaminated water in order to provide real-time feedback of an IoT-based water pollution monitoring system. Water picture categorization is difficult as collected images have large intra-class and minimal inter-class differences. Motivated by the capacity to derive very distinctive characteristics from Convolutional Neural Networks (CNNs), We wish to construct an attention neural network for the classification of gathered water photographs that appropriately encodes channel-wise and multi-layer characteristics in order to accomplish feature representation augmentation. Before building a local and global hierarchical attention neural network, we propose the VGG 19 model with a channel-wise attention gate structure. We carried out comparative experiments with a water surface image dataset from many publications, proving the effectiveness of the proposed attention neural network for classifying water photos. We integrated the proposed neural network as an essential part of an image-based water pollution monitoring system, allowing users to monitor water pollution breaches in real time and take timely corrective action. |
| Keywords: | Water Treatment, CNN, Image Analysis, Water Quality, Machine Learning for Environmental Applications, Deep Learning Classification, VGG19 |
| Cite Article: | "Empowering Water Treatment Through Convolutional Neural Network Classification", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.h400-h415, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404747.pdf |
| Downloads: | 00026 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2404747 Registration ID: 219374 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: h400-h415 Country: Greater Noida , Uttar Pradesh , India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404747 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404747 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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