Weakly supervised label propagation algorithm classifies lung cancer imaging subtypes
X Ren, L Jia, Z Zhao, Y Qiang, W Wu, P Han, J Zhao… - Scientific Reports, 2023 - nature.com
Aiming at the problems of long time, high cost, invasive sampling damage, and easy
emergence of drug resistance in lung cancer gene detection, a reliable and non-invasive …
emergence of drug resistance in lung cancer gene detection, a reliable and non-invasive …
Visual sensor network stimulation model identification via Gaussian mixture model and deep embedded features
Visual sensor networks (VSNs) constitute a fundamental class of distributed sensing
systems, with unique complexity and appealing performance features, which …
systems, with unique complexity and appealing performance features, which …
Identification of leek diseases based on deep learning algorithms
L Xu, S Ning, W Zhang, P Xu, F Zhao, B Cao… - Journal of Ambient …, 2023 - Springer
Vegetable diseases and pests continue to be a major threat to food security. Manual
identification is time-consuming and labor-intensive due to the wide variety of diseases and …
identification is time-consuming and labor-intensive due to the wide variety of diseases and …
Deep learning methods for biomedical information analysis
There are many optimization algorithms to help BIA. Hajieskandar et al.(2020) use hybrid
neural networks and a grey wolf algorithm. Lu et al.(2020) propose a diagnosis system …
neural networks and a grey wolf algorithm. Lu et al.(2020) propose a diagnosis system …
Possibilistic picture fuzzy product partition C-means clustering incorporating rich local information for medical image segmentation
C Wu, T Liu - Multimedia Tools and Applications, 2024 - Springer
Picture fuzzy C-means clustering is a new computational intelligence method that has more
significant potential advantages than fuzzy clustering in medical image interpretation …
significant potential advantages than fuzzy clustering in medical image interpretation …
Clustering Methods and Tools to Handle High-Dimensional Social Media Text Data
M Amadeus, WAC Castañeda - … of NLP and Deep Learning in Social …, 2023 - igi-global.com
Social media data has changed the way big data is used. The amount of data available
offers more natural insights that make it possible to find relations and social interactions …
offers more natural insights that make it possible to find relations and social interactions …
Construction of psychological warning mechanism for college students in big data environment
X HE, F CHEN - Chinese Journal of Medical Education …, 2021 - pesquisa.bvsalud.org
Combining the psychological" big data" of college students with the data of the
psychological expert database, using data mining algorithm to extract characteristic …
psychological expert database, using data mining algorithm to extract characteristic …
Dual deep clustering
Deep clustering is a branch of deep learning, in which the dimensionality reduction
capabilities of deep networks are exploited for clustering data. In this sense, the deep part of …
capabilities of deep networks are exploited for clustering data. In this sense, the deep part of …
Gradient-Based Competitive Learning: Theory
Deep learning has been recently used to extract the relevant features for representing input
data also in the unsupervised setting. However, state-of-the-art techniques focus mostly on …
data also in the unsupervised setting. However, state-of-the-art techniques focus mostly on …