作者:
Khadse, ShrikantGourshettiwar, PalashPawar, Adesh
Faculty of Engineering and Technology Wardha442001 India
Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Wardha442001 India
Department of Computer Science and Medical Engineering Maharashtra Wardha442001 India
Meta-learning aims to create Artificial Intelligence (AI) systems that can adapt to new tasks and improve their performance over time without extensive retraining. The advent of meta-learning paradigms has fundamental...
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The primary cause of mortality in youngsters aged below five is pneumonia, a lung condition. In 2016, a UNICEF survey found that infants under the five-year-old limit made up around 16% of fatalities. Most of the affl...
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Wireless sensor networks(WSNs)are projected to have a wide range of applications in the *** fundamental problem with WSN is that it has afinite *** a network is a common strategy for increasing the life-time of WSNs an...
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Wireless sensor networks(WSNs)are projected to have a wide range of applications in the *** fundamental problem with WSN is that it has afinite *** a network is a common strategy for increasing the life-time of WSNs and,as a result,allowing for faster data *** cluster-ing algorithm’s goal is to select the best cluster head(CH).In the existing system,Hybrid grey wolf sunflower optimization algorithm(HGWSFO)and optimal clus-ter head selection method is *** does not provide better competence and out-put in the ***,the proposed Hybrid Grey Wolf Ant Colony Optimisation(HGWACO)algorithm is used for reducing the energy utilization and enhances the lifespan of the *** hole method is used for selecting the cluster heads(CHs).The ant colony optimization(ACO)technique is used tofind the route among origin CH and *** open cache of nodes,trans-mission power,and proximity are used to improve the CH *** grey wolf optimisation(GWO)technique is the most recent and well-known optimiser module which deals with grey wolves’hunting activity(GWs).These GWs have the ability to track down and encircle *** GWO method was inspired by this hunting *** proposed HGWACO improves the duration of the net-work,minimizes the power consumption,also it works with the large-scale *** HGWACO method achieves 25.64%of residual energy,25.64%of alive nodes,40.65%of dead nodes also it enhances the lifetime of the network.
In or daily lives, maintaining the security of sensitive information has proven to be very difficult. communications sent frequently through a communication channel like the Internet may catch the attention of cracker...
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The recent improvements in the natural language processing (NLP) field have made it possible to create extremely powerful models such as Generative Pre-trained Transformers (GPT), used for generating human-sounding, c...
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We aim to simplify and optimize the process of generating Hindi captions for visual content using deep learning models. With the advancements in deep learning, generating textual descriptions for images is now possibl...
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As a part of smart city schemes, many governments are developed intelligent methods to improve the quality of living by offering them intelligent services to enhance sustainability, livability, and workability. These ...
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Recently, neural network-based inverse models have been used for multi-objective optimization. The basic idea is to approximate the mapping from the Pareto front to the Pareto set. In general, inverse modeling from a ...
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Colonoscopy is the most important technique for detecting colorectal cancer and its precursors. High miss rates continue to be a problem, leaving many abnormalities undiscovered. Systems for computer-aided diagnosis (...
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Most current online multi-object tracking(MOT)methods include two steps:object detection and data association,where the data association step relies on both object feature extraction and affinity *** often leads to ad...
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Most current online multi-object tracking(MOT)methods include two steps:object detection and data association,where the data association step relies on both object feature extraction and affinity *** often leads to additional computation cost,and degrades the efficiency of MOT *** this paper,we combine the object detection and data association module in a unified framework,while getting rid of the extra feature extraction process,to achieve a better speed-accuracy trade-off for *** that a pedestrian is the most common object category in real-world scenes and has particularity characteristics in objects relationship and motion pattern,we present a novel yet efficient one-stage pedestrian detection and tracking method,named *** particular,CGTracker detects the pedestrian target as the center point of the object,and directly extracts the object features from the feature representation of the object center point,which is used to predict the axis-aligned bounding ***,the detected pedestrians are constructed as an object graph to facilitate the multi-object association process,where the semantic features,displacement information and relative position relationship of the targets between two adjacent frames are used to perform the reliable online *** achieves the multiple object tracking accuracy(MOTA)of 69.3%and 65.3%at 9 FPS on MOT17 and MOT20,*** experimental results under widely-used evaluation metrics demonstrate that our method is one of the best techniques on the leader board for the MOT17 and MOT20 challenges at the time of submission of this work.
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