Crowd management becomes a global concern due to increased population in urban *** management of pedestrians leads to improved use of public *** of pedestrian’s is a major factor of crowd management in public *** are...
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Crowd management becomes a global concern due to increased population in urban *** management of pedestrians leads to improved use of public *** of pedestrian’s is a major factor of crowd management in public *** are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the *** this paper,we have proposed a new method for pedestrian’s behavior *** filter has been used to detect pedestrian’s usingmovement based ***,we have performed occlusion detection and removal using region shrinking method to isolate occluded *** verification is performed on each human silhouette and wavelet analysis and particle gradient motion are extracted for each *** Wolf Optimizer(GWO)has been utilized to optimize feature set and then behavior classification has been performed using the Extreme Gradient(XG)Boost *** has been evaluated using pedestrian’s data from avenue and UBI-Fight datasets,where both have different *** mean achieved accuracies are 91.3%and 85.14%over the Avenue and UBI-Fight datasets,*** results are more accurate as compared to other existing methods.
Diabetic wound takes longer time to heal due to micro and macro-vascular *** longer healing time can lead to infections and other health *** ulcers are one of the most common diabetic *** are one of the leading cause ...
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Diabetic wound takes longer time to heal due to micro and macro-vascular *** longer healing time can lead to infections and other health *** ulcers are one of the most common diabetic *** are one of the leading cause of *** science is continuously striving for improving quality of human life.A recent trend of amalgamation of knowledge,efforts and technological advancement of medical science experts and artificial intelligence researchers,has made tremendous success in diagnosis,prognosis and treatment of a variety of *** wounds are no exception,as artificial intelligence experts are putting their research efforts to apply latest technological advancements in the field to help medical care personnel to deal with diabetic wounds in more effective *** presented study reviews the diagnostic and treatment research under the umbrella of Artificial Intelligence and computational science,for diabetic wound *** for diabetic wound assessment using artificial intelligence is ***,this review is focused on existing and potential contribution of artificial intelligence to improve medical services for diabetic wound *** article also discusses the future directions for the betterment of the field that can lead to facilitate both,clinician and patients.
Damage to the retinal blood vessels is critical in diabetic retinopathy, a progressively emerging health concern that often advances quietly without explicit symptoms. Optical coherence tomography-OCT has emerged as a...
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Damage to the retinal blood vessels is critical in diabetic retinopathy, a progressively emerging health concern that often advances quietly without explicit symptoms. Optical coherence tomography-OCT has emerged as a favored noninvasive imaging technique for diagnosing diabetic retinopathy promptly and accurately. However, timely and precise diagnoses from OCT images are essential in prevention of blindness. Moreover, accurate interpretation of OCT images is challenging. Single model learning debilitates in managing diverse data types and structures, constraining its adaptability to varied environments. Its limitations become apparent in tasks requiring expertise from multiple domains, delaying overall performance. Moreover, learning may exhibit susceptibility to overfitting with large and heterogeneous datasets, resulting in compromised generalization capabilities. In this study, we propose a hybrid learning model for the classification of four distinct classes of retinal diseases in OCT images with improved generalization capabilities. Our hybrid model is constructed upon the well-established architectural foundations of ResNet50 and EfficientNetB0. By pre-training the hybrid model on extensive datasets like ImageNet and then fine-tuning it on publicly available OCT image datasets, we capitalize on the strengths of both architectures. This empowers the hybrid model to excel in discerning intricate image patterns while efficiently extracting hierarchical prediction from various regions within the images. To enhance classification accuracy and mitigate overfitting, we eliminate the fully connected layer from the base model and introduce a concatenate layer to combine two objective learning prediction. A dataset comprising 84,452 OCT images, each expertly graded for illnesses. we conducted training and evaluation of our proposed model, which demonstrated superior performance compared to existing methods, achieving an impressive overall classification accuracy of 97.
The concept of smart houses has grown in prominence in recent *** challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device **...
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The concept of smart houses has grown in prominence in recent *** challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device *** home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical *** paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in *** have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT *** system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing *** have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache *** feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time *** is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation ***,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber *** trial results support the proposed system and demonstrate its potential for use in everyday life.
Food recommendation systems (FRSs) provide personalized food recommendations to users based on their taste preferences. In FRSs, users’ unique taste preferences are influenced by personal history, specific dietary ne...
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作者：
Shiju Thomas, M.Y.Krishna, Addapalli V N
Department of Computer Science Kerala India
Department of Computer Science and Engineering Karnataka Bangalore India
Image disarranging is the process of randomly rearranging picture elements to make the visibility unreadable and break the link among neighboring elements. Pixel values often don't change while they are being scra...
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Large Language Models (LLMs) have evolved into Multimodal Large Language Models (MLLMs), significantly enhancing their capabilities by integrating visual information and other types, thus aligning more closely with th...
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This paper delves into the key characteristics of Autonomous underwater vehicle (AUV) design, highlighting considerations such as hull structure, hydrodynamics, propulsion systems, and sensor integration. The main con...
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The development of Deepfakes has become more prevalent with the rise of Generative Adversarial Networks (GANs). Deepfakes are synthetically created, modified images that have been made to look real;they pose severe so...
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The main objective of this research is to deduce the efficacy of integrated nutrient management (INM) technologies in production of oilseed crops for sustainable development. A great amount of experience is needed in ...
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ISBN:
(纸本)9798331515720
The main objective of this research is to deduce the efficacy of integrated nutrient management (INM) technologies in production of oilseed crops for sustainable development. A great amount of experience is needed in selecting the most effective INM strategy. A new recommendation system to circumnavigate this issue is proposed. It lets farmers decide on the best INM strategy to maximize oilseed crop yield and quality. This system is built on the techniques of advanced machine Learning (ML) and aritifical Intelligence (AI). Oilseed crop date in Tamil Nadu from 1961 to 2019 was used to develop the proposed algorithm. The proposed algorithm for crop yield prediction (CYP) which includes a Soft Voting Ensemble Classifier with weights (SVECWW), a Soft Voting Ensemble Classifier without weights (SVECWOW) along with the SVM technique are compared and contrasted with existing algorithms and also proves that SVECWW outperforms other ML algorithms with an accuracy rate of 97.2%. Furthermore, the Stacked Generalization Ensemble model is employed and compared with another Deep Neural Network (DNN) for the INM crop recommendation system which offers a simple graphical user interface (GUI) for farmers to use and received an accuracy of 97.5%. This GUI enables farmers to access valuable information such as the optimal timing for cultivating oilseed crops, the appropriate types and quantities of organic manures, inorganic fertilizers, and bio-fertilizers required for successful oilseed crop production. The study shows, on its whole, how to create tailored recommendation systems for farmers using GUI models with artificial intelligence and machine learning algorithms. Implementing these systems is expected to significantly improve oilseed crop production and quality significantly, benefiting the whole agricultural sector for sustainable development. Artificial intelligence (AI) makes a recommendation system more accurate and adaptable by looking through complex datasets and patterns
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