A Comparative Study of Azure Custom Vision Versus Google Vision API Integrated into AI Custom Models Using Object Classification for Residential Waste

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(7), P. 3869 - 3869

Published: April 1, 2025

The residential separate collection of waste is the first stage in recyclability for sustainable development. paper focuses on designing and implementing a low-cost automatic sorting bin (RBin) recycling, alleviating user’s classification burden. Next, an analysis two object identification models was conducted to sort materials into categories cardboard, glass, plastic, metal. A major challenge distinguishing between glass plastic due their similar visual characteristics. research assesses performance Azure Custom Vision Service (ACVS) model, which achieves high accuracy training data but underperforms real-time applications, with 95.13%. In contrast, second Waste Sorting Model (CWSM), demonstrates (96.25%) during proves be effective applications. CWSM uses two-tier approach, identifying descriptively using Google API (GVAS) followed by through CWSM, predicate-based custom model. employs LbfgsMaximumEntropyMulti algorithm dataset 1000 records training, divided equally across categories. This study proposes innovative evaluation metric, Weighted Classification Confidence Score (WCCS). results show that outperforms ACVS real-world testing, achieving real 99.75% after applying WCCS. explores importance customized over pre-implemented services when model characteristics not pixel-by-pixel examination.

Language: Английский

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A new approach to MADM problem using interval-valued hesitant Fermatean fuzzy Hamacher operators and statistical variance

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 18, 2025

Water ecological civilization construction (WECC) is regarded as the core and cornerstone of construction. However, a lot uncertainty involved in assessing WECC level, which presents serious intricate difficulties for related multiple- attribute decision-making (MADM) processes. The interval-valued hesitant Fermatean fuzzy set (IVHFFS) powerful tool handling MADM issues. existing approaches, weight calculation involves high data redundancy low computational efficiency. aggregation operators ignore importance attributes their ordered positions. In order to solve these problems, this paper, we propose novel model using (IVHFF) Hamacher operator (AO) statistical variance (SV) calculation. Firstly, SV method given under IVHFFSs, aiming computing objective weights attributes. This greatly reduces improves complexity. Secondly, some IVHFF AOs, such (ordered) weighted averaging operator, geometric hybrid consider significance Thirdly, new based on above information AOs proposed. Finally, comparative study real-world application randomly generated sets also carried out further demonstrate that our outperforms methods.

Language: Английский

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Advancing greenhouse gas emission reduction strategies: Integrating Multi-Criteria Decision-Making with Complex q-Rung Picture Fuzzy Sugeno–Weber Operators

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 151, P. 110621 - 110621

Published: March 29, 2025

Language: Английский

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Selecting a Robust and Efficient Heterogeneous Network in 5G by Utilizing Complex Picture Fuzzy Yager Aggregation Operators

Iranian Journal of Science and Technology Transactions of Electrical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 5, 2025

Language: Английский

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The handling of healthcare waste analysis with an interval-valued Fermatean fuzzy-based decision-making technique

Sustainable Futures, Journal Year: 2025, Volume and Issue: unknown, P. 100581 - 100581

Published: April 1, 2025

Language: Английский

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Solid Waste Management using q-rung Orthopair Fuzzy Decision Making based on Sugeno-Weber Prioritized Operator and EDAS Technique

International Journal of Mathematical Engineering and Management Sciences, Journal Year: 2025, Volume and Issue: 10(4), P. 1123 - 1155

Published: April 18, 2025

The rapidly growing population, urbanization, and advancements in technology have led to a continuous increase both the quantity diversity of solid waste (SW). management SW stands out as an urgent concern, volume garbage places enormous strain on environment. Addressing this issue necessitates use methods (SWMMs). Therefore, paper, we propose new Multiattribute group decision-making (MGDM) method under q-rung orthopair fuzzy numbers (q-ROFNs) environment select optimal sustainable SWMM for effective SW. Firstly, present operational laws q-ROFNs based Sugeno-Weber’s norm, which overcomes shortcomings existing q-ROFNs. After that, proposed q-ROFNs, Sugeno-Weber prioritized weighted arithmetic (q-ROFSWPWA) aggregation operator (AO) aggregating considers priority relationship among Moreover, MGDM q-ROFSWPWA AO EDAS technique. Furthermore, consider case study selecting demonstrate method. We also comparative analysis with methods.

Language: Английский

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A picture fuzzy multi-attribute decision-making approach based on Hamacher Muirhead mean operators

Granular Computing, Journal Year: 2024, Volume and Issue: 9(3)

Published: June 8, 2024

Language: Английский

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Enhancing High Temperature Prediction via Six-Fold Strategy Consensus-Reaching Processes: A Case Study using FY-3E Spatio-Temporal Remote Sensing Satellite Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Journal Year: 2024, Volume and Issue: 17, P. 16377 - 16391

Published: Jan. 1, 2024

Language: Английский

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