This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Datascarcity: Paired natural anguage descriptions of music and corresponding music recordings are extremely scarce, in contrast to the abundance of image/descriptions pairs available online, e.g. in online art galleries or social media. This also makes the evaluation step harder and highly subjective.
Harnessing the power of deeplearning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle – the limited availability of training data. Over the years, various successful deeplearning architectures have been developed for this task, such as U-Net or SegFormer.
Harnessing the power of deeplearning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle the limited availability of training data. Over the years, various successful deeplearning architectures have been developed for this task, such as U-Net or SegFormer.
The pre-train and fine-tune paradigm, exemplified by models like ELMo and BERT, has evolved into prompt-based reasoning used by the GPT family. In information retrieval, where faster inference speed is crucial, lightweight models like Sentence-BERT remain widely used.
Muzic is a “research project on AI music that empowers music understanding and generation with deeplearning and artificial intelligence.” Muzic is a research project from Microsoft that uses deeplearning techniques for music generation and understanding – source.
We organize all of the trending information in your field so you don't have to. Join 15,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content