機械学習:Machine Learning Deep Learning Technologies
Deep learning technology, one of the breakthroughs in artificial intelligence technology and machine learning technology
人工知能:Artificial Intelligence
機械学習:Machine Learning 推論技術:inference Technology Overview of Kernel Methods and Support Vector Machines
On kernel methods, one of the breakthroughs in machine learning technology
推論技術:inference Technology Protected: Classification (4) Group learning(Ensemble Learning, Random Forest) and evaluation of learning results(Cross-validation method)
Algorithms for collective learning for data classification and evaluation of classification results (ensemble learning, bagging, boosting, random forests, cross-validation)
推論技術:inference Technology Protected: Classification (3) Probabilistic Discriminant Function(Logistic, Softmax Regression) and Local Learning(K-nearest neighbor method, kernel density estimation)
Probabilistic discriminant functions and local learning used in classifiers for data classification
推論技術:inference Technology Protected: Classification (2) Optimization process(Gradient Descent Method, Newton’s Method, Perceptron, SVM)
Classification techniques for image recognition for use in digital transformation (DX) and artificial intelligence (AI), perceptron, squared loss (Adakine algorithm), SVM (SGD-SVM algorithm)
推論技術:inference Technology Protected: Classification (1) Algorithm of the classifier(Bayes Decision Rule)
Overview of Classification Algorithms for Image Recognition Used in Digital Transformation (DX) and Artificial Intelligence (AI) (Probabilistic Approach)
推論技術:inference Technology Protected: Coding and pooling (BoVW、GMM)
Specific methods of coding and pooling to integrate local features of image recognition into vectors that can be used for digital transformation (DX) and artificial intelligence (AI) (BoVW, mixture Gaussian distribution (GMM), GMM supervector, Fisher vector, VLAD, VLAT).
推論技術:inference Technology Statistical Feature Extraction(PCA,LDA,PCS,CCA)
Statistical feature extraction (Principal Component Analysis (PCA), Whitening, Fisher Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Partial Least Squares (PLS)) for robust local feature extraction in image recognition used in digital transformation (DX) and artificial intelligence (AI).
推論技術:inference Technology Protected: Local Features (3) About Various Descriptors(SIFT,SURF,BRIEF,BRISK,HGO,GIST)
Overview of local descriptors (SIFT descriptors, CNN, SURF descriptors, BRISK descriptors, HLAC descriptors, GIST descriptors) for local feature extraction, which is the first step in image recognition for use in digital transformation (DX) and artificial intelligence (AI) tasks.
推論技術:inference Technology Protected: Local Features (2) About Various Detectors(Edge, corner and blob detectors)
Overview of various detectors for local feature extraction in image recognition technology that can be used for artificial intelligence (AI) and digital transformation (DX) (edge detector, corner detector, blob detector)