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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,082 datasets
A dataset published on Kaggle, likely containing model weights, training data, or outputs related to a 1D DCGAN with an attention mechanism. The author and organization are unknown. The last update date is unknown.
Piotr Matyba's research paper on paperswithcode details the development of an all-plastic, solution-processed light-emitting device. The work utilizes chemically derived graphene as a transparent cathode and a screen-printable conducting polymer anode to create a metal-free light-emitting electrochemical cell (LEC). This demonstrates a pathway for low-voltage, inexpensive, and efficient organic electronics.
Sneha Kulkarni authored a text-based entry on the paperswithcode platform. The description details the career history of David A. Pendlebury, a citation analyst at Clarivate Analytics, and his involvement in developing bibliometric tools like Essential Science Indicators. The entry discusses the context of bibliometric analysis and its potential misuse in shifting scientific focus.
Aleksandar Sabljić of the Rudjer Boskovic Institute reviewed and evaluated models for estimating the degradability of organic compounds. The report identifies Atkinson’s group contribution method as the most accurate for tropospheric degradation and a PLS model with seven rules for biodegradation. It recommends using multiple methods to achieve reliable environmental fate estimates.
The fourth public release of the complete MIPAS mission data, reprocessed by the European Space Agency using the Level 2 processor version 8.22. It contains geophysical atmospheric data products derived from calibrated middle infrared radiance observations. The dataset is targeted at users of MIPAS V8 data and includes quality guidance, screening information, and algorithm descriptions.
Thirty years of global annual urban dynamics and green recovery data from 1985 to 2015, mapped at a 30-meter resolution. The dataset, created by Yinghuai Huang, includes 224 10-degree grid files for urban expansion and green recovery, plus interpreted validation samples for urban extent in 1985 and 2015.
A scientific paper from the paperswithcode platform authored by J. Lintelmann. It provides a review of chemical substances suspected or known to be endocrine disruptors, covering their biochemical background, mechanisms of action, and test strategies. The paper details physicochemical data like water solubility and Kow, as well as concentrations found in environmental media such as soil, sediment, and water.
Peta J. Mudie of Natural Resources Canada describes lithostratigraphic data from 28 piston and gravity cores recovered from the Alpha Ridge in the Central Arctic Ocean. The cores contain late Cenozoic muds with clastic material and define 16 lithostratigraphic units based on texture, structure, color, and mineral content. Some cores include older Campanian-Maastrichtian diatom ooze and Paleogene volcanic ash units, with paleomagnetic data indicating Late Miocene-Early Pliocene ages.
20 CT scans from COVID-19 patients were used to develop a segmentation model for lungs and infected regions. The model, based on a 3D U-Net architecture, achieved Dice similarity coefficients of 0.956 for lungs and 0.761 for infection. This dataset and model were created by Dominik Müller of the University of Augsburg to address limited public COVID-19 imaging data.
Live specimens of the pteropod Limacina helicina antarctica were extracted from the top 200 meters of the Southern Ocean in early 2008, where aragonite saturation levels were around 1. The dataset likely contains measurements of seawater carbonate chemistry and the proportion of different shell dissolution levels, comparing specimens from aragonite-undersaturated regions with those from supersaturated ones. According to the description, eight days of incubation in aragonite saturation levels of 0.94-1.12 produced equivalent levels of dissolution observed in the natural undersaturated region.
A collection of 30,000 synthetic records designed for analyzing remote and hybrid workforce health, created by ZakyF in March 2026. It focuses on predicting burnout risk within HR and People Analytics contexts to simulate employee wellbeing scenarios without using real personal data.
YoloWorld Thesis Modules is a dataset published on Kaggle. Its platform tags indicate it relates to object detection and computer vision, likely containing image data for a thesis project. The dataset's specific content, scale, and authorship details require verification after download.
A checkpoint for a BERT model likely trained on Chinese text, as indicated by the 'GuwenBert' and 'nomnaocr' components of the title. The dataset is published on Kaggle, but its specific creation date and author are unknown. The title suggests it may be associated with a model training stage (stage0) and epoch 30, batch size 50, version 12.
YOLO Simulador SPLIT7 is a dataset hosted on Kaggle. The title suggests it contains simulated data for training or testing YOLO (You Only Look Once) object detection models. The specific content, scale, and origin of the data are not detailed in the available metadata.
LCNN-LFCC-EP1 is a dataset hosted on Kaggle. Its title suggests a focus on audio feature extraction, likely using LFCC (Linear Frequency Cepstral Coefficients) features for a model such as an LCNN (Light Convolutional Neural Network). The dataset's author, organization, and specific content are not detailed in the available metadata.
Underway surface observations of carbon dioxide, dissolved inorganic carbon, alkalinity, and related chemical and physical variables collected from the NOAA vessel SKOGAFOSS. The data were gathered during nine cruises (SKO402 to SKO416) in the North Atlantic Ocean, North Greenland Sea, and Stellwagen Bank National Marine Sanctuary between February 17, 2004, and January 6, 2005. Denis Pierrot, Kevin F. Sullivan, and Rik Wanninkhof of NOAA's Atlantic Oceanographic and Meteorological Laboratory (AOML) collected the data using barometric pressure sensors, carbon dioxide gas analyzers, equilibrators, and thermosalinographs.
NOAA Ocean Acidification Program monitoring data collected from the North Atlantic continental shelf in October-November 2019. Water samples from three depths at select stations were analyzed for dissolved inorganic carbon, pH, total alkalinity, and nutrients. These measurements support research on the adverse effects of ocean acidification on calcifying organisms and species of commercial interest.
CARINA/58JH19920712 data includes chemical, physical, and profile measurements collected from the JOHAN HJORT research vessel in the North Atlantic Ocean, North Greenland Sea, and Norwegian Sea from July 12 to July 28, 1992. The dataset contains variables such as partial pressure of carbon dioxide, dissolved inorganic carbon, oxygen, nutrients, salinity, and temperature, collected using CTD and bottle instruments. Jón Ólafsson of the Icelandic Marine Research Institute and Johan Blindheim of the Institute of Marine Research - Norway collected these data as part of the CARINA and WOCE AR18b projects.
The North Atlantic Ocean, Gulf of Maine, Georges Bank, and Mid-Atlantic Bight were sampled from 2018-11-02 to 2018-11-12 during the R/V Hugh R. Sharp cruise S11802. This dataset contains dissolved inorganic carbon, total alkalinity, pH, and nutrient variables measured from water samples collected at three depths (surface, mid-depth, and near bottom) at select stations. Data were collected in support of NOAA's Ocean Acidification Program and analyzed by the Atlantic Oceanographic and Meteorological Laboratory and the University of Maine.
Profile and discrete water samples collected during NOAA Ship Gordon Gunter cruise GU1902 from August 15 to August 30, 2019. Measurements include dissolved inorganic carbon, total alkalinity, pH, and nutrients from the North Atlantic Ocean, Gulf of Maine, Georges Bank, and Mid-Atlantic Bight. The data supports the NOAA Ocean Acidification Program's coastal monitoring and research objectives.