Vehicular Ad-hoc networks have gained substantial interest from researchers in recent times. They offer the potential to deploy different applications utilized by intelligent transportation systems, which could improv...
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Computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(DL)methods are more successful than other tra...
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Computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(DL)methods are more successful than other traditional machine learning(ML)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of DL methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.
Underwater image enhancement and object detection has great potential for studying underwater environments. It has been utilized in various domains, including image-based underwater monitoring and Autonomous Underwate...
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Underwater image enhancement and object detection has great potential for studying underwater environments. It has been utilized in various domains, including image-based underwater monitoring and Autonomous Underwater Vehicle (AUV)-driven applications such as underwater terrain surveying. It has been observed that underwater images are not clear due to several factors such as low light, the presence of small particles, different levels of refraction of light, etc. Extracting high-quality features from these images to detect objects is a significant challenging task. To mitigate this challenge, MIRNet and the modified version of YOLOv3 namely Underwater-YOLOv3 (U-YOLOv3) is proposed. The MIRNet is a deep learning-based technology for enhancing underwater images. while using YOLOv3 for underwater object detection it lacks in detection of very small objects and huge-size objects. To address this problem proper anchor box size, quality feature aggregation technique, and during object classification image resizing is required. The proposed U-YOLOv3 has three unique features that help to work with the above specified issue like accurate anchor box determination using the K-means++ clustering algorithm, introduced Spatial Pyramid Pooling (SPP) layer during feature extraction which helps in feature aggregation, and added downsampling and upsampling to improve the detection rate of very large and very small size objects. The size of the anchor box is crucial in detecting objects of different sizes, SPP helps in aggregation of features, while down and upsampling changes sizes of objects during object detection. Precision, recall, F1-score and mAP are used as assessment metrics to assess proposed work. The proposed work compared with SSD, Tiny-YOLO, YOLOv2, YOLOv3, YOLOv4, YOLOv5, KPE-YOLOv5, YOLOv7, YOLOv8 and YOLOv9 single stage object detectors. The experiment on the Brackish and Trash ICRA19 datasets shows that our proposed method enhances the mean average precision for b
One of the most intriguing methods of mitigating the hydrogen embrittlement of steels entails nano-precipitates that can trap H from enriching at vulnerable ***,controversial findings have been reported on whether the...
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One of the most intriguing methods of mitigating the hydrogen embrittlement of steels entails nano-precipitates that can trap H from enriching at vulnerable ***,controversial findings have been reported on whether the incoherent NbC precipitates trap ***,by using in-situ scan-ning Kelvin probe force microscopy(SKPFM),we reveal the dynamic interaction of H with the border area of incoherent NbC nanoprecipitates in *** indicate that the interaction between H flux and the interfaces varies amongst different precipitates,implying that H-trapping behaviours of incoherent NbC precipitates could be intrinsically *** origins underlying the distinct behaviours are analyzed.
This paper examines the development of a virtual factory model to optimize overall equipment effectiveness (OEE) in a planned manufacturing facility. Using digital simulations based on a wood manufacturing setup, AI-d...
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This paper introduces a method for Sensitivity Analysis (SA) which lead to the component selection of Rotational Inertial Navigation Systems (RINS) based on a comprehensive error analysis model. RINS improves traditio...
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This research work presents the design and development of a hybrid electric bicycle with a primary focus on energy conservation. A hybrid electric vehicle combines two or more energy conversion technologies with one o...
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The matrix and the reinforcement both are the lifelines of a composite, and their inherent properties are very significant in determining their applicability toward various industrial applications, due to the fact tha...
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The operational thermal stability of perovskite solar cells (PSCs) is a critical issue hindering their commercialization. Therefore, besides achieving high power conversion efficiency (PCE), understanding and quantify...
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Present work investigates degradation of aqueous cefixime (CFX) using visible light activated sodium persulphate (SPS). The effect of five major parameters viz. pH (3–11), initial concentration of CFX (1–10 mg/...
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