DebrisDebris (UKˈdɛbriː,_ˈdeɪbriː, USdəˈbriː) is rubble, wreckage, ruins, litter and discarded garbage/refuse/trash, scattered remains of something destroyed, or, as in geology, large rock fragments left by a melting glacier, etc. Depending on context, debris can refer to a number of different things. The first apparent use of the French word in English is in a 1701 description of the army of Prince Rupert upon its retreat from a battle with the army of Oliver Cromwell, in England.
Marine ecosystemMarine ecosystems are the largest of Earth's aquatic ecosystems and exist in waters that have a high salt content. These systems contrast with freshwater ecosystems, which have a lower salt content. Marine waters cover more than 70% of the surface of the Earth and account for more than 97% of Earth's water supply and 90% of habitable space on Earth. Seawater has an average salinity of 35 parts per thousand of water. Actual salinity varies among different marine ecosystems.
Marine habitatA marine habitat is a habitat that supports marine life. Marine life depends in some way on the saltwater that is in the sea (the term marine comes from the Latin mare, meaning sea or ocean). A habitat is an ecological or environmental area inhabited by one or more living species. The marine environment supports many kinds of these habitats. Marine habitats can be divided into coastal and open ocean habitats. Coastal habitats are found in the area that extends from as far as the tide comes in on the shoreline out to the edge of the continental shelf.
SeabedThe seabed (also known as the seafloor, sea floor, ocean floor, and ocean bottom) is the bottom of the ocean. All floors of the ocean are known as 'seabeds'. The structure of the seabed of the global ocean is governed by plate tectonics. Most of the ocean is very deep, where the seabed is known as the abyssal plain. Seafloor spreading creates mid-ocean ridges along the center line of major ocean basins, where the seabed is slightly shallower than the surrounding abyssal plain.
Binary classificationBinary classification is the task of classifying the elements of a set into two groups (each called class) on the basis of a classification rule. Typical binary classification problems include: Medical testing to determine if a patient has certain disease or not; Quality control in industry, deciding whether a specification has been met; In information retrieval, deciding whether a page should be in the result set of a search or not. Binary classification is dichotomization applied to a practical situation.
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
LitterLitter consists of waste products that have been discarded incorrectly, without consent, at an unsuitable location. The word litter can also be used as a verb: to litter means to drop and leave objects, often man-made, such as aluminum cans, paper cups, food wrappers, cardboard boxes or plastic bottles on the ground, and leave them there indefinitely or for other people to dispose of as opposed to disposing of them correctly.
Weather satelliteA weather satellite or meteorological satellite is a type of Earth observation satellite that is primarily used to monitor the weather and climate of the Earth. Satellites can be polar orbiting (covering the entire Earth asynchronously), or geostationary (hovering over the same spot on the equator). While primarily used to detect the development and movement of storm systems and other cloud patterns, meteorological satellites can also detect other phenomena such as city lights, fires, effects of pollution, auroras, sand and dust storms, snow cover, ice mapping, boundaries of ocean currents, and energy flows.
HazardA hazard is a potential source of harm. Substances, events, or circumstances can constitute hazards when their nature would allow them, even just theoretically, to cause damage to health, life, property, or any other interest of value. The probability of that harm being realized in a specific incident, combined with the magnitude of potential harm, make up its risk, a term often used synonymously in colloquial speech.
Deep reinforcement learningDeep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to make decisions by trial and error. Deep RL incorporates deep learning into the solution, allowing agents to make decisions from unstructured input data without manual engineering of the state space. Deep RL algorithms are able to take in very large inputs (e.g.
