This study tackles the problem of missing data in migrant datasets by introducing a new framework that combines machine learning techniques with neutrosophic sets. These sets, which can represent uncertainty and ambig...
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Technology is changing how students learn in the 21st century significantly. Integrating mobile devices in teaching, learning, and assessment processes has emerged as an important strategy for improving teaching metho...
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In the Kingdom of Saudi Arabia, visual impairment poses significant challenges for approximately 17.5% of school-aged children, mainly due to refractive errors. These challenges extend to everyday navigation, environm...
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In the Kingdom of Saudi Arabia, visual impairment poses significant challenges for approximately 17.5% of school-aged children, mainly due to refractive errors. These challenges extend to everyday navigation, environmental interaction, and overall life quality. Motivated by the desire to empower visually impaired individuals, who face navigational limitations, difficulties in object recognition, and inadequate assistance from traditional technologies, we propose SightAid. This innovative wearable vision system utilizes a deep learning-based framework, addressing the gaps left by current assistive solutions. Traditional methods, such as canes and GPS devices, often fail to meet the nuanced and dynamic needs of the visually impaired, especially in accurately identifying objects, understanding complex environments, and providing essential real-time feedback for independent navigation. SightAid comprises a seven-phase framework involving data collection, preprocessing, and training of a sophisticated deep neural network with multiple convolutional and fully connected layers. This system is integrated into smart glasses with augmented reality displays, enabling real-time object detection and recognition. Interaction with users is facilitated through audio or haptic feedback, informing them about the location and type of objects detected. A continuous learning mechanism, incorporating user feedback and new data, ensures the system's ongoing refinement and adaptability. For performance assessment, we utilized the MNIST dataset, and an Indoor Objects Detection dataset tailored for the visually impaired, featuring images of everyday objects crucial for safe indoor navigation. SightAid demonstrates remarkable performance with accuracy up to 0.9874, recall values between 0.98 and 0.99, F1-scores ranging from 0.98 to 0.99, and AUC-ROC values reaching as high as 0.9999. These metrics significantly surpass those of traditional methods, highlighting SightAid's potential to substan
Artificial intelligence (AI) significantly influences the systems and applications that underpin modern life. Large datasets are generated from diverse sources. Hence, there is a need for effective data monitoring, pr...
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Thermal stress is a critical failure factor for power electronics components. Hence, when developing a precise digital twin for a power system, it is imperative that thermal models provide a reliable portrayal of the ...
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This research aims to enhance point cloud data and simulate the operations of autonomous vehicles following data refinement. The study utilizes high-resolution point cloud data generated by a mobile mapping system and...
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White leg shrimp is one of the animals that is popularly consumed and exported in Thailand. A lot of farmers cultivate white leg shrimp in many areas. To raise white leg shrimp larvae into mature white leg shrimp that...
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Establishing a system for measuring plant health and bacterial infection is critical in ***,the farmers themselves,who observed them with their eyes and relied on their experience in analysis,which could have been ***...
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Establishing a system for measuring plant health and bacterial infection is critical in ***,the farmers themselves,who observed them with their eyes and relied on their experience in analysis,which could have been *** inspection can determine which plants reflect the quantity of green light and near-infrared using infrared light,both visible and eye using a *** goal of this study was to create algorithms for assessing bacterial infections in rice using images from unmanned aerial vehicles(UAVs)with an ensemble classification *** neural networks in unmanned aerial vehi-cles image were *** convey this interest,the rice’s health and bacterial infec-tion inside the photo were *** project entailed using pictures to identify bacterial illnesses in *** shape and distinct characteristics of each infection were *** symptoms were defined using machine learning and image processing *** steps of a convolution neural network based on an image from a UAV were used in this study to determine whether this area will be affected by *** proposed algorithms can be utilized to classify the types of rice deceases with an accuracy rate of 89.84 percent.
Fine-grained image classification is a challenging research topic because of the high degree of similarity among categories and the high degree of dissimilarity for a specific category caused by different poses and scal...
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Fine-grained image classification is a challenging research topic because of the high degree of similarity among categories and the high degree of dissimilarity for a specific category caused by different poses and scales.A cul-tural heritage image is one of thefine-grained images because each image has the same similarity in most *** the classification technique,distinguishing cultural heritage architecture may be diffi*** study proposes a cultural heri-tage content retrieval method using adaptive deep learning forfine-grained image *** key contribution of this research was the creation of a retrieval mod-el that could handle incremental streams of new categories while maintaining its past performance in old categories and not losing the old categorization of a cul-tural heritage *** goal of the proposed method is to perform a retrieval task for *** learning for new classes was conducted to reduce the re-training *** this step,the original class is not necessary for re-train-ing which we call an adaptive deep learning *** heritage in the case of Thai archaeological site architecture was retrieved through machine learn-ing and image *** analyze the experimental results of incremental learning forfine-grained images with images of Thai archaeological site architec-ture from world heritage provinces in Thailand,which have a similar *** afine-grained image retrieval technique for this group of cultural heritage images in a database can solve the problem of a high degree of similarity among categories and a high degree of dissimilarity for a specific *** proposed method for retrieving the correct image from a database can deliver an average accuracy of 85 *** deep learning forfine-grained image retrieval was used to retrieve cultural heritage content,and it outperformed state-of-the-art methods infine-grained image retrieval.
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