Код товара: 5184372723
Постоплата
Купон на скидку
Visual Information Retrieval using Java and LIRE
Тип книги:
Печать по требованию
О товаре
Перейти к описанию
Автор на обложке
Mathias Lux; Oge Marques
Год выпуска
2026
Тип бумаги в книге
Офсетная
Тип обложки
Мягкая обложка
Тип книги
Печать по требованию
О книге
Печатная книга «Visual Information Retrieval using Java and LIRE» в мягкой обложке, язык - английский. В книге 114 страниц, она напечатана на белой офсетной бумаге плотностью 80 г/м². Формат издания —
55,61 BYN 85,43 BYN
Магазин
Подписаться
Т8
Перейти
4.9
Чат
Заказы
50.4 K
О магазине
Часто задаваемые вопросы
Описание
Visual Information Retrieval using Java and LIREПечатная книга «Visual Information Retrieval using Java and LIRE» в мягкой обложке, язык - английский. В книге 114 страниц, она напечатана на белой офсетной бумаге плотностью 80 г/м². Формат издания — 191x235 мм. Все книги аккуратно упаковываем в прочный трёхслойный непрозрачный картонный конверт.
Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories.
The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community. During the past decade, it was widely recognized that the challenges imposed by the lack of coincidence between an image's visual contents and its semantic interpretation, also known as semantic gap, required a clever use of textual metadata (in addition to information extracted from the image's pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on.
In this introductory book, we focus on a subset of VIR problems where the media consists of images, and the indexing and retrieval methods are based on the pixel contents of those images -- an approach known as content-based image retrieval (CBIR). We present an implementation-oriented overview of CBIR concepts, techniques, algorithms, and figures of merit. Most chapters are supported by examples written in Java, using Lucene (an open-source Java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source Java-based library for CBIR.
Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories.
The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community. During the past decade, it was widely recognized that the challenges imposed by the lack of coincidence between an image's visual contents and its semantic interpretation, also known as semantic gap, required a clever use of textual metadata (in addition to information extracted from the image's pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on.
In this introductory book, we focus on a subset of VIR problems where the media consists of images, and the indexing and retrieval methods are based on the pixel contents of those images -- an approach known as content-based image retrieval (CBIR). We present an implementation-oriented overview of CBIR concepts, techniques, algorithms, and figures of merit. Most chapters are supported by examples written in Java, using Lucene (an open-source Java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source Java-based library for CBIR.
- Артикул
- 5184372723
- Автор на обложке
- Mathias Lux; Oge Marques
- Год выпуска
- 2026
- Тип бумаги в книге
- Офсетная
- Тип обложки
- Мягкая обложка
- Тип книги
- Печать по требованию
- Язык издания
- Английский
- Количество страниц
- 114
- Размеры, мм
- 191x235
- Вес товара, г
- 250
- ISBN
- 9781608459186
- Возрастные ограничения
- 12+
Подборки товаров в категории Книги: Компьютерные технологии
Отзывы о товаре
0
Visual Information Retrieval using Java and LIRE
Рейтинга пока нет. Он формируется на основе актуальных отзывов на заказанные и оплаченные товары
Как правильно задавать вопросы?
Будьте вежливы и спрашивайте о товаре, на карточке которого вы находитесь
Если вы обнаружили ошибку в описанием товара, воспользуйтесь функцией
Как отвечать на вопросы?
Отвечать на вопросы могут клиенты, купившие товар, и официальные представители.
Выбрать «Лучший ответ» может только автор вопроса, если именно этот ответ ему помог.