For example, a U-Net [31] model can be used for some studies have utilized manually annotated images for deep semantic segmentation, and a Convolutional Neural Network learning applications involving microplastics, their datasets are (CNN) can then classify the segmented pixels, as demonstrated not publicly accessible [22], [23], [25]. Notably, there is only in [22], [24]. It is also possible to perform instance segmentation one other open-source Scanning Electron Microscopy (SEM) directly from the start. For instance, a Mask R-CNN dataset on microplastics, presented in [24], which categorizes model can simultaneously identify regions of interest, classify particles by shape (e.g., fragments, fibers, and beads) and each detected object, and generate a mask for each instance, features a more limited size distribution. These contributions as shown by [23]. Additionally, Faster R-CNN, primarily used not only address the urgent environmental issue of microplastic for object detection, has been applied to microscopic images to contamination but also set a new benchmark for detecting and classify microplastics into two polymer types [25]. Given the analyzing microplastics in aquatic environments, paving the nature of our dataset, where overlapping and crowded MNPs way for future innovations in the field.

While sorting your plastic recycling might be frustrating, scientists warn that a lack of waste collection could be deadly for millions around the world. Scientists from the University of Leeds have used AI modelling to reveal the 10 countries responsible for the most plastic pollution. Overall, the researchers calculate that 52 million tonnes of uncollected plastic waste entered the environment in 2020, creating a serious health risk for those exposed. India topped the table as the biggest producer of plastic pollution - creating 9.3 million tonnes of waste in a single year - followed by Nigeria and Indonesia. Lead author Dr Costas Velis says: 'This is an urgent global human health issue -- an ongoing crisis: people whose waste is not collected have no option but to dump or burn it.'

You've seen the art AI image generators can create, and you may have played with natural language AI chatbots. You've benefited from artificial intelligence tools recommending you music and suggesting your next streaming show. But AI can do much more. Humans are excellent at spotting patterns. It's why we see faces on Mars or in the clouds.

A fish-shaped robot that'swims' around quickly picking up microplastics has been created by scientists. The tiny machine'wiggles' its body and'flaps' its tail fins to move through water, and could be used to help clear the oceans of plastic pollution. It measures just half-an-inch in length, meaning it can reach into tiny cracks and crevices to collect plastic pieces that would otherwise be inaccessible. Developed by a team at the Sichuan University in China, the robot has no power source, but moves thanks to flashes of near-infrared light. When the light is shone onto to the'fishtail' it bends away from the surface, and when the light is switched off it flops back, propelling the robot through the water.

The world's oceans are critically important to life on Earth. They produce at least 50% of the planet's oxygen, absorb about 30% of the carbon dioxide produced by humans, and their biodiversity can also help protect against the effects of climate change. Millions of people's daily lives are dependent on our oceans -- over 3 billion people rely on fish as a primary source of protein, and 60 million people are directly employed by the fishing industry. The health of our oceans is at significant risk. Pollution, global warming, and overfishing are just some of the threats to this critical life source.

Developed by Minderoo Foundation, the'Global Plastic Watch' tool uses advanced satellite data technology and machine learning to create a near-real-time, high resolution map of plastic pollution. The tool aims to help authorities better manage plastic leakage into the marine environment, and is said to provide the largest ever open source dataset of plastic waste across dozens of countries. Global Plastic Watch uses remote sensing satellite imagery from the European Space Agency and a novel machine learning model created in collaboration with digital product agency Earthrise Media. The tool can determine the size and scale of land-based plastic waste sites, which fuel the growing issue of plastic pollution in the world's rivers and oceans. By using the data, governments, industry and communities can evaluate and monitor the risk of land-based plastic waste sites as well as prioritise investment in solutions, Minderoo Foundation said.

Plastic waste dumped in landfill could be cleared sooner than expected, after engineers developed an enzyme that can break it down in just a few hours. Millions of tons of plastic is left abandoned every year, pilling up in landfills and pollution the land and waterways - typically taking centuries to degrade. A team from the University of Texas in Austin created a new enzyme variant that can supercharge recycling on a large scale, reducing the impact of plastic pollution. The work focusing on PET (polyethylene terephthalate), which is a polymer found in most consumer plastic including bottles, packaging and some textiles. The enzyme was able to complete a'circular process' of breaking down the plastic into smaller parts and chemically putting it back together in as little as 24 hours. They've called it FAST-PETase (functional, active, stable, and tolerant PETase), developed from a natural PETase that allows bacteria to degrade and modify plastic.

Plastic waste is a significant environmental pollutant that is difficult to monitor. We created a system of neural networks to analyze spectral, spatial, and temporal components of Sentinel-2 satellite data to identify terrestrial aggregations of waste. The system works at continental scale. We evaluated performance in Indonesia and detected 374 waste aggregations, more than double the number of sites found in public databases. The same system deployed across twelve countries in Southeast Asia identifies 996 subsequently confirmed waste sites. For each detected site, we algorithmically monitor waste site footprints through time and cross-reference other datasets to generate physical and social metadata. 19% of detected waste sites are located within 200 m of a waterway. Numerous sites sit directly on riverbanks, with high risk of ocean leakage.

You can guarantee that any beach you walk on, you'll find pieces of plastic," said James Comerford, a senior researcher in materials and nanotechnology at SINTEF, an independent research organisation in Oslo, Norway. Plastics are estimated to comprise 85% of marine litter, with 11 million metric tonnes entering the oceans annually and the volume potentially tripling by 2040. Some have predicted that, by weight, there will be more plastics than fish in the seas by 2050. In light of the alarming outlook, innovative approaches are required to tackle the problem. This is exactly what the EU Mission "Restore our Ocean and Waters by 2030" is targeting, with the ambition of reducing plastic litter at sea by at least 50%, cutting microplastics released into the environment by 30%, and halving agricultural nutrient losses as well as the use of chemical pesticides. To reduce pollution, the Mission is launching a'lighthouse' in the Mediterranean Sea that will act as a hub to develop, ...

You can guarantee that any beach you walk on, you'll find pieces of plastic,' said James Comerford, a senior researcher in materials and nanotechnology at SINTEF, an independent research organisation in Oslo, Norway. Plastics are estimated to comprise 85% of marine litter, with 11 million metric tonnes entering the oceans annually and the volume potentially tripling by 2040. Some have predicted that, by weight, there will be more plastics than fish in the seas by 2050. In light of the alarming outlook, innovative approaches are required to tackle the problem. This is exactly what the EU Mission "Restore our Ocean and Waters by 2030" is targeting, with the ambition of reducing plastic litter at sea by at least 50%, cutting microplastics released into the environment by 30%, and halving agricultural nutrient losses as well as the use of chemical pesticides.