Insect fine-grained image classification is an application scenario in fine-grained image classification. It not only has the characteristics of small inter-class differences and large intra-class differences, but als...
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Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) ar...
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Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.
Indian stock market is unique with high volatility and complexity, so special approaches are needed for its computational understanding. This study proposes Temporal Relational Network (TRNet), a new Graph Neural Netw...
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The objective of this study is to forecast the future price movements of equities listed on the National Stock Exchange (NSE) of India. To anticipate the future price movement, all prior statistical and machine learni...
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Most existing NAS-based multi-modal classification (MMC-NAS) methods are optimized using the classification *** can not simultaneously provide multiple models with diverse perferences such as model complex and classif...
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There are numerous applications for detecting stress states from physiological inputs. Human stress detection may be used to enhance the human experience as well as monitor and prevent stress-related disorders. Previo...
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Agriculture plays a foremost role in countries growth. The physical recognition of disease in the plant is more timeconsuming and necessity of expert labor is high. One of the most vital aspect in agriculture field is...
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Blockchain is a decentralised, distributed public ledger that has recently garnered enormous traction. The automotive industry, one of the most profitable markets worldwide, is undoubtedly responsible for the transfor...
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Multifunctional therapeutic peptides(MFTP)hold immense potential in diverse therapeutic contexts,yet their prediction and identification remain challenging due to the limitations of traditional methodologies,such as e...
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Multifunctional therapeutic peptides(MFTP)hold immense potential in diverse therapeutic contexts,yet their prediction and identification remain challenging due to the limitations of traditional methodologies,such as extensive training durations,limited sample sizes,and inadequate generalization *** address these issues,we present AMHF-TP,an advanced method for MFTP recognition that utilizes attention mechanisms and multi-granularity hierarchical features to enhance *** AMHF-TP is composed of four key components:a migration learning module that leverages pretrained models to extract atomic compositional features of MFTP sequences;a convolutional neural network and selfattention module that refine feature extraction from amino acid sequences and their secondary structures;a hypergraph module that constructs a hypergraph for complex similarity representation between MFTP sequences;and a hierarchical feature extraction module that integrates multimodal peptide sequence *** with leading methods,the proposed AMHF-TP demonstrates superior precision,accuracy,and coverage,underscoring its effectiveness and robustness in MFTP *** comparative analysis of separate hierarchical models and the combined model,as well as with five contemporary models,reveals AMHFTP’s exceptional performance and stability in recognition tasks.
Depression is a typical condition that impacts 3.8 % in total population, with 5.0 % of adults and 5.7 % of oldaged persons suffering from it. Depression can be dangerous to one's health, especially if it is persi...
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