Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence
원문 초록
This article reviews the "Once learning" mechanism that was proposed 23 years ago and the subsequent successes of "One-shot learning" in image classification and "You Only Look Once - YOLO" in objective detection. Analyzing the current development of Artificial Intelligence (AI), the proposal is that AI should be clearly divided into the following categories: Artificial Human Intelligence (AHI), Artificial Machine Intelligence (AMI), and Artificial Biological Intelligence (ABI), which will also be the main directions of theory and application development for AI. As a watershed for the branches of AI, some classification standards and methods are discussed: 1) Human-oriented, machine-oriented, and biological-oriented AI R&D; 2) Information input processed by Dimensionality-up or Dimensionality-reduction; 3) The use of one/few or large samples for knowledge learning.
함께 살펴볼 논문
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Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image Classification
Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification
Multi-direction Networks with Attentional Spectral Prior for Hyperspectral Image Classification
Fuzzy Pooling
Beyond the Attention: Distinguish the Discriminative and Confusable Features For Fine-grained Image Classification
Multiscale Context-Aware Ensemble Deep KELM for Efficient Hyperspectral Image Classification
토론
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