Predicting molecular properties is crucial across scientific and industrial domains such as drug discovery and material science. Contrastive learning has gained prominence as an effective method. However, routine stra...
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The study in this paper centers on the prediction of the propagation delay of the eLoran system on the Xi'an-Chengdu path, focusing on the influence of meteorological factors on the propagation delay. First, the s...
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Lung cancer is considered as one of the most significant causes of deaths globally. Diagnosis at an initial stage, using computed tomography chest scans could give a better chance to the patient to survive by providin...
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To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated *** fundus imaging(CFI)is a screening technology that is both effective and *** to CFIs,the early stages of the d...
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To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated *** fundus imaging(CFI)is a screening technology that is both effective and *** to CFIs,the early stages of the disease are characterized by a paucity of observable symptoms,which necessitates the prompt creation of automated and robust diagnostic *** traditional research focuses on image-level diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of *** addition,they usually only target one or a few different kinds of eye diseases at the same *** this study,we design a patient-level multi-label OD(PLML_ODs)classification model that is based on a spatial correlation network(SCNet).This model takes into consideration the relevance of patient-level diagnosis combining bilateral eyes and multi-label ODs ***_ODs is made up of three parts:a backbone convolutional neural network(CNN)for feature extraction i.e.,DenseNet-169,a SCNet for feature correlation,and a classifier for the development of classification *** DenseNet-169 is responsible for retrieving two separate sets of attributes,one from each of the left and right *** then,the SCNet will record the correlations between the two feature sets on a pixel-by-pixel *** the attributes have been analyzed,they are integrated to provide a representation at the patient *** the whole process of ODs categorization,the patient-level representation will be *** efficacy of the PLML_ODs is examined using a soft margin loss on a dataset that is readily accessible to the public,and the results reveal that the classification performance is significantly improved when compared to several baseline approaches.
Automatic speech recognition (ASR) for the Turkish language faces significant challenges due to its agglutinative structure and diverse phonetic variations. In this study, we evaluate the performance of OpenAI's W...
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In recent years, we have witnessed the generation of exceptional authentic deepfake images and videos due to the availability of cutting-edge Artificial Intelligence and deep learning techniques. Deepfakes represent s...
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This paper proposes a novel method for early action prediction based on 3D skeleton data. Our method combines the advantages of graph convolutional networks (GCNs) and adversarial learning to avoid the problems of ins...
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This paper proposes a novel method for early action prediction based on 3D skeleton data. Our method combines the advantages of graph convolutional networks (GCNs) and adversarial learning to avoid the problems of insufficient spatio-temporal feature extraction and difficulty in predicting actions in the early execution stage of actions. In our method, GCNs, which have outstanding performance in the field of action recognition, are used to extract the spatio-temporal features of the skeleton. The model learns how to optimize the feature distribution of partial videos from the features of full videos through adversarial learning. Experiments on two challenging action prediction datasets show that our method performs well on skeleton-based early action prediction. State-of-the-art performance is reported in some observation ratios.
Aiming at the problem of energy consumption optimization in multi-robot path planning, this paper presents a multi-robot path planning algorithm based on optimal energy consumption. First, we improve the traditional A...
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In the MIS (minimally invasive surgery), precise measurement and mastery of human organs is very important, even a slight wobble of instrument can cause a great deal of error. Digital 3D reconstruction technology can ...
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The trajectory tracking performance of flexible joint robots (FJRs) is adversely affected in the presence of measurement noise, unmodelled system dynamics, external disturbances, and parametric variations. This paper ...
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