Edge AI

Artificial Intelligence 分類

2024

11-01

Edge AI

11-01

Model Trustworthiness

10-31

Randomness techniques in deep neural networks

10-23

Label Noise Learning

10-23

Generalization

10-18

電腦視覺、影像處理和圖形識別的關聯

09-22

常見降維方法 - PCA、tSNE、UMAP

02-26

Feature Decoupling

02-23

Dual Learning

02-23

Contrastive Learning

01-23

Explainable Artificial Intelligence

2023

12-27

Classification evaluation metrics

12-20

Federated AI Technology Enabler

12-13

Fairness Machine Learning

12-09

Trusted Execution Environment

12-09

Homomorphic Encryption

12-09

Secure Multi-Party Computation

12-09

Differential Privacy

12-09

Vanilla Federated Learning

12-08

PySyft

11-27

Fed-BioMed

11-20

Backdoor Watermarking

08-31

Sparsity Learning

08-29

Manifold Learning

08-21

Adversarial Machine Learning

08-14

Representation learning

08-08

Trustworthy AI with Causality Perspectives

07-26

TensorRT

07-24

Chain-Of-Thought Prompting

07-18

Machine Learning

07-17

Active Learning

07-06

Lightweight Network Models

07-06

Automated Machine Learning

07-06

Automated Mixed Precision

06-30

Optimization in Deep Learning

06-19

Image Registration

06-19

Image Segmentation

06-19

Multi-Modal Learning

06-19

Incremental Learning

06-19

Transfer Learning

06-19

Knowledge Adaptation

06-19

Knowledge Amalgamation

06-16

Distributed Machine Learning

06-15

Image Quality Assessment

05-18

Uncertainty

05-09

Knowledge Distillation

05-09

Federated Learning

05-04

JAX

05-04

Network Architecture Search (NAS)

05-03

Model Compression and Acceleration for Deep Learning

05-03

Zero-shot, One-shot和Few-shot的差異

05-03

Self Supervised Learning

05-03

Meta Learning

05-03

人工智慧2.0

2022

11-19

卷積神經網路發展文獻探討

09-27

CSPNet 解析

02-04

Res2Net 解析

2021

12-11

凍結參數

12-11

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