Search Results for "weight scale software"
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Showing 20 open source projects for "weight scale software"
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Image Harmonization Dataset iHarmony4
The first large-scale public benchmark dataset for image harmonization
This repository provides the iHarmony4 dataset, which is a large-scale dataset designed for image harmonization tasks. Image harmonization involves adjusting the appearance of a foreground in a composite image so that it is consistent with the background (in color, tone, illumination, etc.). The iHarmony4 dataset comprises four sub-datasets (HCOCO, HAdobe5k, HFlickr, Hday2night), each making composite images by combining a foreground from one image with a background from another, along with... -
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X's Recommendation Algorithm
Source code for the X Recommendation Algorithm
The Algorithm is Twitter’s open source release of the core ranking system that powers the platform’s home timeline. It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. Written primarily in... -
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Exclusively Dark Image Dataset
ExDARK dataset is the largest collection of low-light images
The Exclusively Dark (ExDARK) dataset is one of the largest curated collections of real-world low-light images designed to support research in computer vision tasks under challenging lighting conditions. It contains 7,363 images captured across ten different low-light scenarios, ranging from extremely dark environments to twilight. Each image is annotated with both image-level labels and object-level bounding boxes for 12 object categories, making it suitable for detection and classification... -
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DomainBed
DomainBed is a suite to test domain generalization algorithms
DomainBed is a PyTorch-based research suite created by Facebook Research for benchmarking and evaluating domain generalization algorithms. It provides a unified framework for comparing methods that aim to train models capable of performing well across unseen domains, as introduced in the paper In Search of Lost Domain Generalization. The library includes a wide range of well-known domain generalization algorithms, from classical baselines such as Empirical Risk Minimization (ERM) and... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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MOA - Massive Online Analysis
Big Data Stream Analytics Framework.
A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning. -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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CountBitsSet
minimal benchmark code for Counting Set Bits (ones) in an Integer
I was curious how much better the Algorithms, pointed out by BitTwiddling Hacks, perform than a simple Lookup Table approach... Now I think, perhaps my little investigation is interesting for others too... PS: the parallel counting Algo is about 35% faster on average on my computers than a simple LUT based solution. Also this shows nicely how different a human brain compatible solution is to a binary machine optimal solution :-) In the meantime I added other Algorithms beside... -
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NTU RGB-D
Info and sample codes for "NTU RGB+D Action Recognition Dataset"
The “NTU RGB+D” repository provides access to a large-scale dataset for human action recognition (and its extension, NTU RGB+D 120). The dataset includes multiple modalities (RGB video, depth sequences, infrared video, 3D skeletal joint data) captured with multiple Kinect v2 cameras simultaneously. The repository also contains MATLAB / Python demo scripts for loading, visualizing, and processing skeleton data, mapping between modalities, and handling dataset structure. Multi-modal action... -
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Mr.FSM
Large-Scale Frequent Subgraph Mining in MapReduce
This is the program used in the following paper: Wenqing Lin, Xiaokui Xiao, and Gabriel Ghinita. Large-Scale Frequent Subgraph Mining in MapReduce. In Proceedings of the 30th IEEE International Conference on Data Engineering (ICDE), pages 844-855, 2014. Please cite the paper if you choose to use the program. If having any problems, please report to {wlin1 at ntu dot edu dot sg}. -
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A light-weight Regular Expression (regex) C library, using double-recursion. (command prompt tester included)
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BudgetedSVM
BudgetedSVM: A C++ Toolbox for Large-scale, Non-linear Classification
We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classi fication problems with millions of... -
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drvq
dimensionality-recursive vector quantization
drvq is a C++ library implementation of dimensionality-recursive vector quantization, a fast vector quantization method in high-dimensional Euclidean spaces under arbitrary data distributions. It is an approximation of k-means that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a by-product of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast. A detailed README file describes the usage of the software, including license, requirements, installation, file formats, sample data, tools, and options. ... -
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PPSeq: Parallel NGS Analysis
Parallel Processing for Next-Generation Sequencing (NGS) Analysis
High-throughput next generation sequencing (NGS) technology has quickly emerged as a powerful tool in many aspects of biomedical research. However, along with its rapid development, the data magnitude and analysis complexity for NGS far exceed the capacity and capability of traditional small-scale computing facilities, such as multithreading algorithms on standalone workstations. To address this issue, here we present a solution using the ever-increasing supply of processing power by massive... -
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A capsule tree is a general purpose, self-balancing tree data structure for large, ordered, data-sets. It is designed to provide the same characteristics as B-trees and B+trees, but built from the ground up for in-memory usage. In other words, there are no provisions for “slow” I/O cases. The original motivation for this tree was a better backend for memory managers. However, the end result was a new sub-category of trees. The implementation giving here is just one implementation of...
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A light-weight group communication system/library of distributed algorithms implementations for agreement problems (e.g., Consensus, Unreliable Leader Election and Atomic Broadcast).
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SPLITNEURON is a completely new approach to large-scale, biologically plausible, neural-network simulation library based on data structures and methods directly coded into database and conceived to explicitly share load on multiple machines.
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libconhash is a consistent hashing libraray, which can be compiled both on Windows and Linux platform. High performance, easy to use, and easy to scale according to node's processing capacity.
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The C++ library Geneva allows to run large scale parametric optimization problems. It can run in serial or multi-threaded mode or in a networked environment. The library currently covers Evolutionary Strategies, Genetic Algorithms and mixed scenarios.
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On open source MPI implementation of parallel bucket sorting. This implementation is scalable and gives linear speedup on SGI(Altix). The program sorts at using the bits and hence is stronger than other sorters which make assumptions about keys.
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A collection of Concurrent and Highly Scalable Utilities. These are intended as direct replacements for the java.util.* or java.util.concurrent.* collections but with better performance when many CPUs are using the collection concurrently.
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