$Arxiv preprint generation and jounral sharing rules$

Arxiv preprint generation and jounral sharing rules

For a wider impression on the community, we often publish our manuscript to the public (e.g., arxiv) before it is accepted by a journal.

2022-09-20

Scientific Research/科研

scientific research 科研 PhD graduate school plan

Object detection and detection heads 2

Object detection and detection heads 2

We are continuing to talk about regression/classification based detection framework.

2022-09-12

Machine learning Deep learning Computer vision

object detection detection heads

Object detection and detection heads

Object detection and detection heads

Object detection has a significant relationship with video analysis and image understanding. Region selection is an essential part of object detection. Usually, we call it a (detection) head to distin

2022-09-09

Machine learning Deep learning Computer vision

object detection detection heads

Classification vs. localisation vs. semantic segmentation vs. instance segmentation

Classification vs. localisation vs. semantic segmentation vs. instance segmentation

I am confused about segmentation, localisation, and tracking from time to time. Therefore, I want to take some notes and summarise the differences among them.

2022-06-04

Machine learning Deep learning

segmentation classification localisation tracking

Self-supervised learning learns representations from the physical nature

Self-supervised learning learns representations from the physical nature

Self-supervised visual representation learning is a method that learns the physical essence of nature objectives. It is a promising subclass of unsupervised learning.

2022-05-29

Machine learning Deep learning

self-supervised nature

Word embedding - Class review

Word embedding - Class review

We use word embedding to feature representation. The contents of the blog are a note rearranging of course Sequence Model.

2022-05-26

Machine learning Deep learning

word embedding representations

Unsupervised learning can learn from features without label

Unsupervised learning can learn from features without label

Unsupervised learning can learn features by specifically designed loss without any pre-labels. There are two most common seen unsupervised learning methods, which are autoencoder and GANs. In this art

2022-05-18

Machine learning Deep learning

unsupervised learning

Weakly supervised learning has various diversities of labels

Weakly supervised learning has various diversities of labels

Weak supervision has three types, incomplete supervision, inexact supervision, and inaccurate supervision. Weakly supervised learning is generally defined as a learning framework under inadequate supe

2022-05-17

Machine learning Deep learning

deep learning weakly-supervised learning

One server can collaborate with global clients using federated learning

One server can collaborate with global clients using federated learning

Live data of humans and other natural mechanisms are constantly generated every day. With the development of human living standards and perceptron, new types of data will be updated. Thus, there is a

2022-05-15

Machine learning Deep learning

federated learning federated averaging

Semi-supervised learning and its goal

Semi-supervised learning and its goal

Semi-supervised learning is a learning paradigm concerned with how to learn the presence of both labelled and unlabelled data.

2022-05-14

Machine learning Deep learning

semi-supervised