|
Reverse Image Search
Reverse image search is a content-based image retrieval (CBIR) query technique that involves providing the CBIR system with a sample image that it will then base its search upon; in terms of information retrieval, the sample image is very useful in its ways. In particular, reverse image search is characterized by a lack of search terms. This effectively removes the need for a user to guess at keywords or terms that may or may not return a correct result. Reverse image search also allows users to discover content that is related to a specific sample image, popularity of an image, and discover manipulated versions and derivative works. Uses Reverse image search may be used to: * Locate the source of an image. * Find higher resolution versions. * Discover webpages where the image appears. * Find the content creator. * Get information about an image. Algorithms Commonly used reverse image search algorithms include: * Scale-invariant feature transform - to extract local features of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Kubernetes
Kubernetes (, commonly stylized as K8s) is an open-source container orchestration system for automating software deployment, scaling, and management. Google originally designed Kubernetes, but the Cloud Native Computing Foundation now maintains the project. Kubernetes works with Containerd, and CRI-O. Originally, it interfaced exclusively with the Docker runtime through a "Dockershim"; however, from November 2020 up to April 2022, Kubernetes has deprecated the shim in favor of directly interfacing with the container through Containerd, or replacing Docker with a runtime that is compliant with the Container Runtime Interface (CRI). With the release of v1.24 in May 2022, "Dockershim" has been removed entirely. History Kubernetes ( κυβερνήτης, Greek for "helmsman," "pilot," or "governor", and the etymological root of cybernetics) was announced by Google in mid-2014. The project was created by Joe Beda, Brendan Burns, and Craig McLuckie, who were soon joined by other ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Feature Extraction
In machine learning, pattern recognition, and image processing, feature extraction starts from an initial set of measured data and builds derived values (features) intended to be informative and non-redundant, facilitating the subsequent learning and generalization steps, and in some cases leading to better human interpretations. Feature extraction is related to dimensionality reduction. When the input data to an algorithm is too large to be processed and it is suspected to be redundant (e.g. the same measurement in both feet and meters, or the repetitiveness of images presented as pixels), then it can be transformed into a reduced set of features (also named a feature vector). Determining a subset of the initial features is called feature selection. The selected features are expected to contain the relevant information from the input data, so that the desired task can be performed by using this reduced representation instead of the complete initial data. General Feature extractio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache HBase
HBase is an open-source non-relational distributed database modeled after Google's Bigtable and written in Java. It is developed as part of Apache Software Foundation's Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System) or Alluxio, providing Bigtable-like capabilities for Hadoop. That is, it provides a fault-tolerant way of storing large quantities of sparse data (small amounts of information caught within a large collection of empty or unimportant data, such as finding the 50 largest items in a group of 2 billion records, or finding the non-zero items representing less than 0.1% of a huge collection). HBase features compression, in-memory operation, and Bloom filters on a per-column basis as outlined in the original Bigtable paper. Tables in HBase can serve as the input and output for MapReduce jobs run in Hadoop, and may be accessed through the Java API but also through REST, Avro or Thrift gateway APIs. HBase is a wide-column store and has been w ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cascading (software)
Cascading is a software abstraction layer for Apache Hadoop and Apache Flink. Cascading is used to create and execute complex data processing workflows on a Hadoop cluster using any JVM-based language (Java, JRuby, Clojure, etc.), hiding the underlying complexity of MapReduce jobs. It is open source and available under the Apache License. Commercial support is available from Driven, Inc. Cascading was originally authored by Chris Wensel, who later founded Concurrent, Inc, which has been re-branded as Driven. Cascading is being actively developed by the community and a number of add-on modules are available. Architecture To use Cascading, Apache Hadoop must also be installed, and the Hadoop job .jar must contain the Cascading .jars. Cascading consists of a data processing API, integration API, process planner and process scheduler. Cascading leverages the scalability of Hadoop but abstracts standard data processing operations away from underlying map and reduce tasks. Develope ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Convolutional Neural Network
In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of artificial neural network (ANN), most commonly applied to analyze visual imagery. CNNs are also known as Shift Invariant or Space Invariant Artificial Neural Networks (SIANN), based on the shared-weight architecture of the convolution kernels or filters that slide along input features and provide translation-equivariant responses known as feature maps. Counter-intuitively, most convolutional neural networks are not invariant to translation, due to the downsampling operation they apply to the input. They have applications in image and video recognition, recommender systems, image classification, image segmentation, medical image analysis, natural language processing, brain–computer interfaces, and financial time series. CNNs are regularized versions of multilayer perceptrons. Multilayer perceptrons usually mean fully connected networks, that is, each neuron in one layer is connected to all neuro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Hadoop
Apache Hadoop () is a collection of open-source software utilities that facilitates using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data using the MapReduce programming model. Hadoop was originally designed for computer clusters built from commodity hardware, which is still the common use. It has since also found use on clusters of higher-end hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common occurrences and should be automatically handled by the framework. The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part which is a MapReduce programming model. Hadoop splits files into large blocks and distributes them across nodes in a cluster. It then transfers packaged code into nodes to process the data in parallel. This a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SIGKDD
SIGKDD, representing the Association for Computing Machinery's (ACM) Special Interest Group (SIG) on Knowledge Discovery and Data Mining, hosts an influential annual conference. Conference history The KDD Conference grew from KDD (Knowledge Discovery and Data Mining) workshops at AAAI conferences, which were started by Gregory I. Piatetsky-Shapiro in 1989, 1991, and 1993, and Usama Fayyad in 1994. Conference papers of each Proceedings of the SIGKDD International Conference on Knowledge Discovery and Data Mining are published through ACM. KDD is widely considered the most influential forum for knowledge discovery and data mining research. The KDD conference has been held each year since 1995, and SIGKDD became an official ACM Special Interest Group in 1998. Past conference locations are listed on the KDD conference web site. The annual ACM SIGKDD conference is recognized as a flagship venue in the field. Based on statistics provided by independent researcher Lexing Xie in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Association For Computing Machinery
The Association for Computing Machinery (ACM) is a US-based international learned society for computing. It was founded in 1947 and is the world's largest scientific and educational computing society. The ACM is a non-profit professional membership group, claiming nearly 110,000 student and professional members . Its headquarters are in New York City. The ACM is an umbrella organization for academic and scholarly interests in computer science ( informatics). Its motto is "Advancing Computing as a Science & Profession". History In 1947, a notice was sent to various people: On January 10, 1947, at the Symposium on Large-Scale Digital Calculating Machinery at the Harvard computation Laboratory, Professor Samuel H. Caldwell of Massachusetts Institute of Technology spoke of the need for an association of those interested in computing machinery, and of the need for communication between them. ..After making some inquiries during May and June, we believe there is ample interest to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pinterest
Pinterest is an American image sharing and social media service designed to enable saving and discovery of information (specifically "ideas") on the internet using images, and on a smaller scale, animated GIFs and videos, in the form of pinboards. The site was created by Ben Silbermann, Paul Sciarra, and Evan Sharp, and had 433 million global monthly active users as of July 2022. It is operated by Pinterest, Inc., based in San Francisco. History The idea for ''Pinterest'' emerged from an earlier app created by Ben Silberman and Paul Sciarra called Tote which served as a virtual replacement for paper catalogs. Tote struggled as a business, significantly due to difficulties with mobile payments. At the time, mobile payment technology was not sophisticated enough to enable easy on-the-go transactions, inhibiting users from making many purchases via the app. Tote users were, however, amassing large collections of favorite items and sharing them with other users. The behavior struck ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
