Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics. The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use. In spite of the fact that these two schools both have ‘linguistics’ in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings.

Semantics --- Natural Language Processing --- Computational Linguistics --- Artificial Intelligence --- explainable AI --- Artificial Neural Nets --- lexical semantics --- word vectors --- embeddings --- dynamic embeddings --- algebraic semantic --- knowledge bases --- machine learning

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics. The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use. In spite of the fact that these two schools both have ‘linguistics’ in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings.

Natural language & machine translation --- Computational linguistics --- Artificial intelligence --- Machine learning --- Expert systems / knowledge-based systems --- Literature: history & criticism --- Semantics --- Natural Language Processing --- Computational Linguistics --- Artificial Intelligence --- explainable AI --- Artificial Neural Nets --- lexical semantics --- word vectors --- embeddings --- dynamic embeddings --- algebraic semantic --- knowledge bases --- machine learning

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis.

interpretable/explainable machine learning --- image classification --- image processing --- machine learning models --- white box --- black box --- cancer prediction --- deep learning --- multimodal learning --- convolutional neural networks --- autism --- fMRI --- texture analysis --- melanoma --- glcm matrix --- machine learning --- classifiers --- explainability --- explainable AI --- XAI --- medical imaging --- diagnosis --- ARMD --- change detection --- unsupervised learning --- microwave breast imaging --- image reconstruction --- tumor detection --- digital pathology --- whole slide image processing --- multiple instance learning --- deep learning classification --- HER2 --- medical images --- transfer learning --- optimizers --- neo-adjuvant treatment --- tumour cellularity --- cancer --- breast cancer --- diagnostics --- imaging --- computation --- artificial intelligence --- 3D segmentation --- active surface --- discriminant analysis --- PET imaging --- medical image analysis --- brain tumor --- cervical cancer --- colon cancer --- lung cancer --- computer vision --- musculoskeletal images --- lung disease detection --- taxonomy --- convolutional neural network --- CycleGAN --- data augmentation --- dermoscopic images --- domain transfer --- macroscopic images --- skin lesion segmentation --- infection detection --- COVID-19 --- X-ray images --- bayesian inference --- shifted-scaled dirichlet distribution --- MCMC --- gibbs sampling --- object detection --- surgical tools --- open surgery --- egocentric camera --- computers in medicine --- segmentation --- MRI --- ECG signal detection --- portable monitoring devices --- 1D-convolutional neural network --- medical image segmentation --- domain adaptation --- meta-learning --- U-Net --- computed tomography (CT) --- magnetic resonance imaging (MRI) --- low-dose --- sparse-angle --- quantitative comparison --- interpretable/explainable machine learning --- image classification --- image processing --- machine learning models --- white box --- black box --- cancer prediction --- deep learning --- multimodal learning --- convolutional neural networks --- autism --- fMRI --- texture analysis --- melanoma --- glcm matrix --- machine learning --- classifiers --- explainability --- explainable AI --- XAI --- medical imaging --- diagnosis --- ARMD --- change detection --- unsupervised learning --- microwave breast imaging --- image reconstruction --- tumor detection --- digital pathology --- whole slide image processing --- multiple instance learning --- deep learning classification --- HER2 --- medical images --- transfer learning --- optimizers --- neo-adjuvant treatment --- tumour cellularity --- cancer --- breast cancer --- diagnostics --- imaging --- computation --- artificial intelligence --- 3D segmentation --- active surface --- discriminant analysis --- PET imaging --- medical image analysis --- brain tumor --- cervical cancer --- colon cancer --- lung cancer --- computer vision --- musculoskeletal images --- lung disease detection --- taxonomy --- convolutional neural network --- CycleGAN --- data augmentation --- dermoscopic images --- domain transfer --- macroscopic images --- skin lesion segmentation --- infection detection --- COVID-19 --- X-ray images --- bayesian inference --- shifted-scaled dirichlet distribution --- MCMC --- gibbs sampling --- object detection --- surgical tools --- open surgery --- egocentric camera --- computers in medicine --- segmentation --- MRI --- ECG signal detection --- portable monitoring devices --- 1D-convolutional neural network --- medical image segmentation --- domain adaptation --- meta-learning --- U-Net --- computed tomography (CT) --- magnetic resonance imaging (MRI) --- low-dose --- sparse-angle --- quantitative comparison

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis.

interpretable/explainable machine learning --- image classification --- image processing --- machine learning models --- white box --- black box --- cancer prediction --- deep learning --- multimodal learning --- convolutional neural networks --- autism --- fMRI --- texture analysis --- melanoma --- glcm matrix --- machine learning --- classifiers --- explainability --- explainable AI --- XAI --- medical imaging --- diagnosis --- ARMD --- change detection --- unsupervised learning --- microwave breast imaging --- image reconstruction --- tumor detection --- digital pathology --- whole slide image processing --- multiple instance learning --- deep learning classification --- HER2 --- medical images --- transfer learning --- optimizers --- neo-adjuvant treatment --- tumour cellularity --- cancer --- breast cancer --- diagnostics --- imaging --- computation --- artificial intelligence --- 3D segmentation --- active surface --- discriminant analysis --- PET imaging --- medical image analysis --- brain tumor --- cervical cancer --- colon cancer --- lung cancer --- computer vision --- musculoskeletal images --- lung disease detection --- taxonomy --- convolutional neural network --- CycleGAN --- data augmentation --- dermoscopic images --- domain transfer --- macroscopic images --- skin lesion segmentation --- infection detection --- COVID-19 --- X-ray images --- bayesian inference --- shifted-scaled dirichlet distribution --- MCMC --- gibbs sampling --- object detection --- surgical tools --- open surgery --- egocentric camera --- computers in medicine --- segmentation --- MRI --- ECG signal detection --- portable monitoring devices --- 1D-convolutional neural network --- medical image segmentation --- domain adaptation --- meta-learning --- U-Net --- computed tomography (CT) --- magnetic resonance imaging (MRI) --- low-dose --- sparse-angle --- quantitative comparison --- n/a

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The notion of smart and sustainable cities offers an integrated and holistic approach to urbanism by aiming to achieve the long-term goals of urban sustainability and resilience. In essence, a smart and sustainable city is an urban locality that functions as a robust system of systems with sustainable practices to generate desired outcomes and futures for all humans and non-humans. This book contributes to improving research and practice in smart and sustainable metropolitan as well as regional cities and urbanism by bringing together literature reviews and scholarly perspective pieces, forming an open access knowledge warehouse. It contains contributions that offer insights into research and practice in smart and sustainable metropolitan and regional cities by producing in-depth conceptual debates and perspectives, insights from the literature and best practice, and thoroughly identified research themes and development trends. This book serves as a repository of relevant information, material, and knowledge to support research, policymaking, practice, and the transferability of experiences to address challenges in establishing smart and sustainable metropolitan as well as regional cities and urbanism in the era of climate change, biodiversity collapse, natural disasters, pandemics, and socioeconomic inequalities.

Research & information: general --- Environmental economics --- regional towns --- regional cities --- regional Australia --- regional lifestyle location --- regional innovation system --- regional turnaround --- post-pandemic urban growth --- COVID-19 impact --- regional planning --- sustainable urban development --- smart cities --- blockchain --- building information management (BIM) --- city information management (CIM) --- sustainable building --- life cycle --- VOSviewer --- commuting --- employment --- housing price --- GDP --- income --- big data --- prediction --- urbanization --- sustainability --- corporate social responsibility --- ready-made garments --- framework for strategic sustainable development --- Bangladesh --- PCB shield --- HX711 --- amplifier chip --- Sim900A --- e-commerce --- virtual store --- firmware --- embedded system --- virtual reality and haptic sensing --- urban sustainability --- sustainable behavior --- sustainability understanding --- awareness --- perception --- attitude --- pro-environmental behavior --- influencing factors --- Turkey --- Istanbul --- sustainable city --- sustainable development --- environmental performance --- online platform --- municipalities --- artificial intelligence (AI) --- green AI --- sustainable AI --- responsible AI --- ethical AI --- explainable AI --- AI regulation --- green sensing --- sustainable development goals --- waste sorting --- supply chain redesigning --- function allocation --- path planning --- incinerable waste --- smart city --- smart city industry --- industrial ecosystem --- input-output analysis --- structural path analysis --- knowledge-based development --- knowledge-based urban development --- smart and sustainable city --- local development --- urban development --- knowledge cities world summit --- international events --- Bento Gonçalves --- Brazil --- technology --- governance --- knowledge workers --- knowledge precincts --- open data --- Gold Coast --- digital engineering --- information requirements --- infrastructure asset management --- technology integration matrix --- master-planned estate --- community --- community identity --- social connectedness --- social infrastructure: physical infrastructure --- housing developments --- longitudinal study --- social capital --- neighbourhoods --- sustainable social development --- ecological study --- ordinal logistic regression --- northern Sweden --- regional towns --- regional cities --- regional Australia --- regional lifestyle location --- regional innovation system --- regional turnaround --- post-pandemic urban growth --- COVID-19 impact --- regional planning --- sustainable urban development --- smart cities --- blockchain --- building information management (BIM) --- city information management (CIM) --- sustainable building --- life cycle --- VOSviewer --- commuting --- employment --- housing price --- GDP --- income --- big data --- prediction --- urbanization --- sustainability --- corporate social responsibility --- ready-made garments --- framework for strategic sustainable development --- Bangladesh --- PCB shield --- HX711 --- amplifier chip --- Sim900A --- e-commerce --- virtual store --- firmware --- embedded system --- virtual reality and haptic sensing --- urban sustainability --- sustainable behavior --- sustainability understanding --- awareness --- perception --- attitude --- pro-environmental behavior --- influencing factors --- Turkey --- Istanbul --- sustainable city --- sustainable development --- environmental performance --- online platform --- municipalities --- artificial intelligence (AI) --- green AI --- sustainable AI --- responsible AI --- ethical AI --- explainable AI --- AI regulation --- green sensing --- sustainable development goals --- waste sorting --- supply chain redesigning --- function allocation --- path planning --- incinerable waste --- smart city --- smart city industry --- industrial ecosystem --- input-output analysis --- structural path analysis --- knowledge-based development --- knowledge-based urban development --- smart and sustainable city --- local development --- urban development --- knowledge cities world summit --- international events --- Bento Gonçalves --- Brazil --- technology --- governance --- knowledge workers --- knowledge precincts --- open data --- Gold Coast --- digital engineering --- information requirements --- infrastructure asset management --- technology integration matrix --- master-planned estate --- community --- community identity --- social connectedness --- social infrastructure: physical infrastructure --- housing developments --- longitudinal study --- social capital --- neighbourhoods --- sustainable social development --- ecological study --- ordinal logistic regression --- northern Sweden