Question 1

Which countries lead Domain Adaptation and Few-Shot Learning research?

Accepted Answer

By volume, China and the United States publish the most (7.4k and 1.6k works in 2022-now).

Question 2

Which institutions lead Domain Adaptation and Few-Shot Learning research?

Accepted Answer

By volume in 2022-now, Chinese Academy of Sciences publishes the most Domain Adaptation and Few-Shot Learning research, followed by University of Electronic Science and Technology of China and Xidian University.

Question 3

Who are the leading researchers in Domain Adaptation and Few-Shot Learning?

Accepted Answer

The most-cited researchers publishing on Domain Adaptation and Few-Shot Learning include Kaiming He, Yoshua Bengio and Geoffrey E. Hinton.

Question 4

Where is Domain Adaptation and Few-Shot Learning research done?

Accepted Answer

The largest centres of Domain Adaptation and Few-Shot Learning research in 2022-now are Beijing (China), Shanghai (China), Xi'an (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Shanghai, Shenzhen and Mountain View.

Question 5

Where is the best place to study Domain Adaptation and Few-Shot Learning?

Accepted Answer

Among universities, judged by research, Nanyang Technological University, Northwestern Polytechnical University and Hong Kong University of Science and Technology score highest, combining citation excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

Question 6

Is Domain Adaptation and Few-Shot Learning research growing?

Accepted Answer

Output in 2022-2025 was 93% higher than in 2018-2021, peaking in 2023. The fastest-growing topics are Domain Adaptation and Few-Shot Learning.

Question 7

What are the most cited papers in Domain Adaptation and Few-Shot Learning?

Accepted Answer

The most cited paper in Domain Adaptation and Few-Shot Learning is "Deep Residual Learning for Image Recognition" (Kaiming He, Xiangyu Zhang, Shaoqing Ren et al., 2016), with 229,585 citations. Next come "Long Short-Term Memory" (102,418) and "ImageNet classification with deep convolutional neural networks" (75,634).