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Found 9 papers, 0 papers with code
Density-based Isometric Mapping
Multiple imaging datasets overall of 72, 236 cases, 70, 000 MINST data, 1596 from multiple Chest-XRay pneumonia datasets, and three NSCLC CT/PET datasets with a total of 640 lung cancer patients, were used to benchmark and validate PR-Isomap.
AI-Enabled Lung Cancer Prognosis
Lung cancer is the primary cause of cancer-related mortality, claiming approximately 1. 79 million lives globally in 2020, with an estimated 2. 21 million new cases diagnosed within the same period.
Distribution-based Low-rank Embedding
These findings suggest that JSE and Weibull embedding techniques substantially help preserve crucial thermal patterns as a biomarker leading to improved CBE and enabling the very early detection of breast cancer.
Embedded Deep Regularized Block HSIC Thermomics for Early Diagnosis of Breast Cancer
In this study, an embedding method is proposed to address this problem and Deep-semi-nonnegative matrix factorization (Deep-SemiNMF) for thermography is introduced, then tested for 208 breast cancer screening cases.
Low-rank Convex/Sparse Thermal Matrix Approximation for Infrared-based Diagnostic System
Active and passive thermography are two efficient techniques extensively used to measure heterogeneous thermal patterns leading to subsurface defects for diagnostic evaluations.
Skeletonization and Reconstruction based on Graph Morphological Transformations
Multiscale shape skeletonization on pixel adjacency graphs is an advanced intriguing research subject in the field of image processing, computer vision and data mining.
Mathematical Morphology via Category Theory
With enriching Mat over various semirings such as Boolean and (max,+) semirings, one can arrive at classical definition of binary and gray-scale images using the categorical tensor product in Mat.
Bio-Inspired Human Action Recognition using Hybrid Max-Product Neuro-Fuzzy Classifier and Quantum-Behaved PSO
Studies on computational neuroscience through functional magnetic resonance imaging (fMRI) and following biological inspired system stated that human action recognition in the brain of mammalian leads two distinct pathways in the model, which are specialized for analysis of motion (optic flow) and form information.
A Dual Fast and Slow Feature Interaction in Biologically Inspired Visual Recognition of Human Action
Form features in the visual system biologically follows the application of active basis model with incremental slow feature analysis for the extraction of the slowest form features of human objects movements in the ventral stream.
