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Former Somali pirate Chief 'Afweyne' given 20-year sentence.

Brendan Smialowski | AFP | Getty Images President Donald Trump speaks to reporters before walking to Marine One on the South Lawn of the White House November 29, 2018 in Washington, DC. President Donald Trump postponed a Saturday press conference designed to tout the "great success" of the Group of 20 meeting in Argentina, citing…

A combination of factors including stepped up naval patrols closer to shore is leading to a drop in pirate attacks off the Somali coast, the former commander of NATO's counter-piracy mission said Monday (17 December).

Adverse weather conditions such as rain and haze often lead to a degradation in the quality of maritime images, which is crucial for activities like navigation, fishing, and search and rescue. Therefore, it is of great interest to develop an effective algorithm to recover high-quality maritime images under adverse weather conditions. This paper proposes a prompt-based learning method with degradation perception for maritime image restoration, which contains two key components: a restoration module and a prompting module. The former is employed for image restoration, whereas the latter encodes weather-related degradation-specific information to modulate the restoration module, enhancing the recovery process for improved results. Inspired by the recent trend of prompt learning in artificial intelligence, this paper adopts soft-prompt technology to generate learnable visual prompt parameters for better perceiving the degradation-conditioned cues. Extensive experimental results on several benchmarks show that our approach achieves superior restoration performance in maritime image dehazing and deraining tasks.