2 天前 - … A detailed review of feature extraction in image processing systems. In: 2014 Fourth
International Conference on Advanced Computing & Communication Technologies. IEEE; …

2 天前 - … [19] concluded that errors in data analysis and model selection … deep learning
model, which effectively integrates domain knowledge and potential features extracted from deep …

2 天前 - … and metabolite retention times were used to determine α-PiHP use. (2) Classification
… were developed using principal component analysis for feature extraction and logistic …

2 天前 - … [19] recently introduced a novel IRT data analysis method termed Thermal … for
extracting features from data obtained by IRT and its use as an input attribute for machine-learning…

2 天前 - … In this paper, we present a TCN-SA module as a feature extraction channel for
multi-dimensional meteorological data. The convolution layer and recursive structure of TCN can …

2 天前 - … deep learning techniques appear very powerful in cancer classification and feature
extraction through the learning … these data deficiencies in gene expression data analysis [23…

2 天前 - … feature learning network, a hash learning block, and a spatial attention block to
enhance feature extraction … In general, image retrieval using deep learning algorithms showed …

2 天前 - … deep learning in medical domains, challenges still remain owing to data scarcity,
compounded by privacy concerns and data … with semantic feature extraction capabilities. (3) …

2 天前 - … With the development of deep learning technology, neural networks have been …
Each ht i,j denotes extracted deep temporal feature of the j-th nodes xj at time t, relying …

2 天前 - … utilization of multimodal data by subsequent machine learning modules [9]. … We
used a single RTX 3090 for training. For unimodal feature extraction from text data, we use pre-…