Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things
In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
Measuring self-regulated learning and the role of AI: Five years of research using multimodal multichannel data
Learning sciences are embracing the significant role technologies can play to better detect,
diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with …
diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with …
Beyond transmitting bits: Context, semantics, and task-oriented communications
Communication systems to date primarily aim at reliably communicating bit sequences.
Such an approach provides efficient engineering designs that are agnostic to the meanings …
Such an approach provides efficient engineering designs that are agnostic to the meanings …
Wireless deep video semantic transmission
In this paper, we design a new class of high-efficiency deep joint source-channel coding
methods to achieve end-to-end video transmission over wireless channels. The proposed …
methods to achieve end-to-end video transmission over wireless channels. The proposed …
Scalable image coding for humans and machines
At present, and increasingly so in the future, much of the captured visual content will not be
seen by humans. Instead, it will be used for automated machine vision analytics and may …
seen by humans. Instead, it will be used for automated machine vision analytics and may …
Task-oriented image transmission for scene classification in unmanned aerial systems
The vigorous developments of the Internet of Things make it possible to extend its computing
and storage capabilities to computing tasks in the aerial system with the collaboration of …
and storage capabilities to computing tasks in the aerial system with the collaboration of …
Learning end-to-end lossy image compression: A benchmark
Image compression is one of the most fundamental techniques and commonly used
applications in the image and video processing field. Earlier methods built a well-designed …
applications in the image and video processing field. Earlier methods built a well-designed …
Fitvid: Overfitting in pixel-level video prediction
An agent that is capable of predicting what happens next can perform a variety of tasks
through planning with no additional training. Furthermore, such an agent can internally …
through planning with no additional training. Furthermore, such an agent can internally …
Towards end-to-end image compression and analysis with transformers
We propose an end-to-end image compression and analysis model with Transformers,
targeting to the cloud-based image classification application. Instead of placing an existing …
targeting to the cloud-based image classification application. Instead of placing an existing …
Image coding for machines with omnipotent feature learning
Abstract Image Coding for Machines (ICM) aims to compress images for AI tasks analysis
rather than meeting human perception. Learning a kind of feature that is both general (for AI …
rather than meeting human perception. Learning a kind of feature that is both general (for AI …