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Scalable AI and Design Patterns Design, Develop, and Deploy Scalable AI Solutions
Understand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's...
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Conformal predictions for probabilistically robust scalable machine learning classification
Conformal predictions make it possible to define reliable and robust learning algorithms. But they are essentially a method for evaluating whether an...
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Introduction to Scalable AI Systems
Artificial intelligence (AI) is rapidly altering many facets of our lives, from personalized suggestions on streaming platforms to self-driving cars...
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Development of scalable coding of encrypted images using Modified Absolute Moment Block Truncation Code
Many researchers have worked on scalable coding for unencrypted images, and there is more space for research in scalable coding for encrypted images....
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A scalable blockchain storage scheme for VANET
Intelligent transportation systems (ITSs) make it possible for applications such as autonomous driving, active safety systems and smart cities. As...
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Scalable image compression algorithms with small and fixed-size memory
The SPIHT image compression algorithm is characterized by low computational complexity, good performance, and the production of a quality scalable...
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Scalable short-entry dual-grain coherence directories with flexible region granularity
As the number of cores in a chip multiprocessor increase, the directory size becomes excessive. Current research shows that directory size can be...
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Scalable Affine Multi-view Subspace Clustering
Subspace clustering (SC) exploits the potential capacity of self-expressive modeling of unsupervised learning frameworks, representing each data...
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Studying Drowsiness Detection Performance While Driving Through Scalable Machine Learning Models Using Electroencephalography
Driver drowsiness is a significant concern and one of the leading causes of traffic accidents. Advances in cognitive neuroscience and computer...
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Scalable AI Deployment and Productionization
Scalable AI deployment and productionization are all about bringing artificial intelligence's enormous potential into practice. It's like owning a...
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Scalable Supervised Asymmetric Hashing
Learning compact hash codes is widely employed for rapid similarity search, capitalizing on reduced storage requirements and efficient query speeds....
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Scalable AI Infrastructure and Architecture
Assume you're constructing a house. You begin with a small, cozy cabin but expect your family to grow. As a result, you plan the foundation,...
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Scalable decoupling graph neural network with feature-oriented optimization
Recent advances in data processing have stimulated the demand for learning graphs of very large scales. Graph neural networks (GNNs), being an...
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Scalable AI Algorithms and Models
Artificial intelligence (AI) is becoming increasingly prevalent. AI is changing the way we live and work, from chatbots that assist with customer...
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Formal modelling and verification of scalable service composition in IoT environment
A system based on the internet of things (IoT) consists of services deployed across several devices that collaborate to fulfil IoT system goals. The...
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Scalable AI for Edge Computing
AI empowers machines to mimic human intelligence, while edge computing brings computational power closer to the data source, reducing latency and...
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Data Engineering for Scalable AI
In today's digital world, data is everywhere. Data is being generated at an unprecedented rate, from your social media interactions to Internet...
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Apache Spark-based scalable feature extraction approaches for protein sequence and their clustering performance analysis
Genome sequencing projects are rapidly contributing to the rise of high-dimensional protein sequence datasets. Extracting features from a...
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A novel apache spark-based 14-dimensional scalable feature extraction approach for the clustering of genomics data
Feature extraction is essential in bioinformatics because it transforms genomics sequences into feature vectors, which are needed for clustering to...
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Scalable image coding with enhancement features for human and machine
The past decade has seen significant advancements in computer vision technologies, resulting in an increasing consumption of images and videos by...
