Search Results for "dataset" - Page 19
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Showing 643 open source projects for "dataset"
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The GAN Zoo
A list of all named GANs
...Because new GAN models are frequently introduced in research publications, the repository serves as a convenient catalog that organizes them in one location. The list includes references to many GAN variants along with links to their original research papers and sometimes implementation code. Users can browse the dataset or explore a tabular version that allows filtering by year or searching for specific model names. The repository encourages contributions from the community so that newly published GAN architectures can be added to the list. -
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BossSensor
Hide screen when boss is approaching
...The software relies on libraries such as OpenCV, TensorFlow, and Python-based machine learning tools to perform face detection and classification. Training the system requires a dataset of labeled images representing the boss and other people so that the model can learn to differentiate between them. -
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MarDRe
MapReduce-based tool to remove duplicate DNA reads
MarDRe is a de novo MapReduce-based parallel tool to remove duplicate and near-duplicate DNA reads through the clustering of single-end and paired-end sequences from FASTQ/FASTA datasets. This tool allows bioinformatics to avoid the analysis of not necessary reads, reducing the time of subsequent procedures with the dataset. MarDRe is the Big Data counterpart of ParDRe (link above), which employs HPC technologies (i.e., hybrid MPI/multithreading) to reduce runtime on multicore systems. Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. ... -
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Exposure
Learning infinite-resolution image processing with GAN and RL
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model. ACM Transactions on Graphics (presented at SIGGRAPH 2018) Exposure is originally designed for RAW photos, which assumes 12+ bit color depth and linear "RGB" color space (or whatever we get after demosaicing). jpg and png images typically have only 8-bit color depth (except 16-bit pngs) and the lack of information (dynamic range/activation resolution) may... -
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3D ResNets for Action Recognition
3D ResNets for Action Recognition (CVPR 2018)
We uploaded the pretrained models described in this paper including ResNet-50 pretrained on the combined dataset with Kinetics-700 and Moments in Time. We significantly updated our scripts. If you want to use older versions to reproduce our CVPR2018 paper, you should use the scripts in the CVPR2018 branch. -
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Mixup-CIFAR10
mixup: Beyond Empirical Risk Minimization
...By interpolating both data and labels, the model learns smoother decision boundaries and becomes more robust to noise and adversarial examples. This repository implements mixup for the CIFAR-10 dataset, showcasing its effectiveness in improving generalization, stability, and calibration of neural networks. The approach acts as a regularizer, encouraging linear behavior in the feature space between samples, which helps reduce overfitting and enhance performance on unseen data. -
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lottie vectors
Create, display and process 2D vectors in a 3D window.
...This could be a common math symbol or greek letter, start/end signposts, or a number of the position either from the begining or after a reset. After all the information has been loaded for your dataset. Either passed over the command line, or as a text file. Lottie Vectors displays inside a figure that you can resize, rotate and turn 2D positions into a 3D picture. -
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Learn_Deep_Learning_in_6_Weeks
This is the Curriculum for "Learn Deep Learning in 6 Weeks"
Learn_Deep_Learning_in_6_Weeks compresses an introductory deep learning curriculum into six weeks of structured learning and practice. It begins with neural network fundamentals and moves through convolutional and recurrent architectures, optimization strategies, regularization, and transfer learning. The materials emphasize code-first understanding: building small models, training them on accessible datasets, and analyzing their behavior. Each week culminates in a tangible outcome—such as a... -
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mzitu
Python crawler that downloads image galleries and analyzes titles
...It focuses on automating the collection of large sets of images by programmatically parsing page content and iterating through gallery entries. mzitu also includes a simple analysis script that processes downloaded folder names to generate statistics and visualizations. Using text segmentation and frequency analysis, the project can create a word cloud representing common keywords found in the dataset. This makes the repository both a scraping example and a small data analysis experiment built around the collected content. Overall, mzitu serves as a learning-oriented implementation of Python web scraping, data processing, and visualization techniques. -
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OYSTER Entity Resolution
OYSTER is an Entity Resolution engine
Entity Resolution is the process by which a dataset is processed and records are identified that represent the same real-world entity. OYSTER (Open sYSTem Entity Resolution) is an entity resolution system that supports probabilistic direct matching, transitive linking, and asserted linking. To facilitate prospecting for match candidates (blocking), the system builds and maintains an in-memory index of attribute values to identities. -
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PMU-UD
handwritten dataset of Urdu/Arabic Numerals
The handwritten dataset was collected from 170 participants with a total of 5,180 numeral patterns. The dataset is named Prince Mohammad Bin Fahd University - Urdu/Arabic Database (PMU-UD). -
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ECDICT
Free English to Chinese Dictionary Database
...Because it’s offline and local, it avoids network latency and licensing hurdles that come with calling proprietary dictionary APIs. The dataset is large enough to support general-purpose lookup while being manageable to ship with desktop or mobile apps. For builders, it’s a pragmatic foundation for dictionary apps, pop-up translators, flashcard tools, or NLP preprocessing. -
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Smart Dataset-XML Viewer (outdated)
Smart viewer for the CDISC Dataset-XML Standard
This the old page for the "Smart Dataset-XML Viewer". It is a Java-based viewer for CDISC Submission files (SDTM, SEND, ADaM) in the new Dataset-XML Format. The Project has been renamed to "Smart Submission Dataset Viewer", and can be found at: https://sourceforge.net/projects/smart-submission-dataset-viewe/ -
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GIU Gallery Image Upload
GIU is mostly a tool to manage the upload of images as well as manage
Output and stored data will be path to image, title of link, link to image, alternative text to image and storyline text. Controls and options such as image width and height plus some template features to control are available in the Controls Panel. GIU is Open Source and I welcome the community to add to this project. The ideology of GIU is to provide a simple use application for end users as well as a robust control panel with adequate administrative operations. Folder structures are... -
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Charting tools, backtesting tools, and data visualization tools for the most popular cryptocurrencies.
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Zhao
A compilation of "The Princely Party Relationship Network"
...Because it aggregates content associated with Zhao, the repository functions as a personal or shared knowledge base for readers who want insight into a body of research rather than a traditional software library. Depending on the specific subfolders, it could offer implementations of algorithms, dataset processing utilities, or notebooks that illustrate concepts. Users interested in reading academic work or numerical demonstrations can use the content to deepen understanding of advanced topics. -
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Gensim-data
Data repository for pretrained NLP models and NLP corpora
...Downloads are cached in a local gensim-data directory for later reuse. The collection includes corpora such as text8 and 20 Newsgroups alongside pretrained word-vector resources such as GloVe. Every dataset retains its own licensing terms, so users must review individual usage conditions. -
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EPISEARCH
Fast, parallelised epistasis detection using information theory
Search for epistatic triples through a genetic dataset. See https://github.com/haqueo/EPISEARCH for setup, documentation and examples. -
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EvalAI
Evaluating state of the art in AI
EvalAI is an open-source platform for evaluating and comparing machine learning (ML) and artificial intelligence (AI) algorithms at scale. We allow the creation of an arbitrary number of evaluation phases and dataset splits, compatibility using any programming language, and organizing results in both public and private leaderboards. Certain large-scale challenges need special computing capabilities for evaluation. If the challenge needs extra computational power, challenge organizers can easily add their own cluster of worker nodes to process participant submissions while we take care of hosting the challenge, handling user submissions, and maintaining the leaderboard. ... -
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DC-TTS
TensorFlow Implementation of DC-TTS: yet another text-to-speech model
...Training scripts, data loaders, and hyperparameter configurations are provided to reproduce results on several datasets, including LJ Speech for English, a Korean single-speaker dataset, and audiobook data from Nick Offerman and Kate Winslet. -
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xmgrace python interface
xmgrace and qtgrace plotting interface in python
This is a python module providing a nearly complete interface to the graphing program xmgrace and the new qtgrace (great project... grace works under windows, too, now!). It allows creation of grace plots from within python, which can be customized using python, or through grace after creation. -
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IGVC IITK Data
Data useful for testing autonomous navigation algorithms
This repository is only used for the purpose of dataset storage for Team IGVC, IITK. For the relevant code, see our GitHub repositories. (https://github.com/igvc-iitk). The recorded data is used for testing various algorithms related to Computer Vision, SLAM, Motion Planning etc. -
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Siamese and triplet learning
Siamese and triplet networks with online triplet mining in PyTorch
Siamese and triplet learning is a PyTorch implementation of Siamese and triplet neural network architectures designed for learning embedding representations in machine learning tasks. These types of networks learn to map images into a compact feature space where the distance between vectors reflects the similarity between inputs. Such embeddings are commonly used in applications like face recognition, image similarity search, and few-shot learning. The repository demonstrates how to train... -
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FastPhotoStyle
Style transfer, deep learning, feature transform
...It is computationally efficient due to its closed-form solution, allowing fast processing compared to iterative optimization-based methods. The framework is particularly useful in applications such as photo editing, film post-processing, and dataset augmentation where realism is critical. By preserving structural details and avoiding distortions, it produces results that are visually consistent with natural images.