gaochang (12 resultados)

Condición: New.

Soft cover. Condición: Fine. Title: 300 Years of Fugui Paintings at Fuxi Jin Museum Gaofeng, Wei Yao, Mao Si, Eka Soo, Kao Zuo, Luo Lan Shan, Xia Jia Yao, Lai Fever, etc. Product: Nine Normal Publication time: 1984 Edition: Soft Cover Publisher: Asahi Shimbun Page size: 199 Page size: 29.7 x 22.5 cm 164 Product Description: Classical and Modern Paintings of Hokoku, 66 oil paintings from the 16th century to the 19th century in this book, Classical Realism, Reachable Impressionism, Inclusive Primitiveism, Revisited Primitiveism, Wild Beasts Modern schools such as the school, the Nabi school, comprehensive Western Mongolian Wudin, Yu Te Luo Yi, Ge Lei Tong, Ke Luo, Mi Le, Mana, Mo Na, Lei Noa, Deka, Lao Te Reike, Sai Shang, Gao Zhao , Wai Yai, Mao Si, Mika Soo, Hua Zhuo, Luo Ran Shan, Xia Jia Yai, Lai Heat and other famous works, each work has a very detailed commentary, a large amount of correlated materials and chronology attached after the book, printing effect Kaya very Fine, original Japanese version. In the 17th century, the law was called the 'great century', and in this period, the rule was 'the sun king'. The stage of the history of calendar history, the stage of the history of calendar history, and the foundation of contemporary law culture. Early 17th-century Hokoku paintings are still influenced by Dairi and Northern Method Randokushi. Immediate arrival of great work in the art world, the vitality of the art world has been created, and the style of the Law Kingdom of the United Kingdom has been created. Reasonableness, quiet and detailed classicism style, enlightened legal golden age of art.

Condición: New.

Soft cover. Condición: Fine. Title: Modern Art at Harvard Artists: Mo Na, Sai Shang, Gaochang, Masiteng. Lai Fever, Xavier Xile, Ma Jing Yue, Luo Si Ke, Mac Si, De Ku Ning, Du Fu Fei, Mo Li Si, Lu Yi Si, Gu Si Pei Qi Si, Lixi Fuji Si Tan, Wu Huo Ya, Luo Dan, Daiei Shimitsu, etc. Quality: Perfect Publication time: 1985 Edition: Soft Hardcover Publisher: Nihon Keizai Shimbun Printing time: 1999 Page count: 234 Page size: 29 x 22.6 cm 164 Description: 20th century contemporary art collection , This book includes Mo Na, Sai Shang, Gao Zhang, Mas Deng. Modern Art Schools such as Ma Singer, Luo Si Ke, Masu Si, Deku Ning, Du Fu Fei, Molisi Luyi Si, Gui Si Pei Qi Si, Li Xi Fu Si Tan, Wu Huo Yao, Luo Dan, Dawei Si Misi etc. 106 painting art master works, of which 91 paintings and 15 sculptures. The author of the abstract painting, the author and the introduction of the work in both English and Japanese after the book, the printing effect of this book is extremely unsatisfactory, and it is possible to see the various creative forms of modern artists among these works. Original Japanese version.

Hardcover. Condición: new. Hardcover. The rapid advancement of deep learning technology has brought about transformative breakthroughs in perception and recognition systems across a wide range of applications. In addition to driving innovation in industrial sectors, it has opened up significant opportunities in fields such as intelligent transportation, smart cities, healthcare, and robotics.Deep learning significantly enhances the accuracy and robustness of perception and recognition systems through hierarchical feature extraction in multilayer neural networks, achieving remarkable results in areas such as soft sensing, image classification, natural language processing, and object detection. By training on large volumes of labeled data, deep learning algorithms are able to automatically learn complex feature representations and efficiently recognize objects during the perception process.As application scenarios grow more complex and data become increasingly diverse, deep learning models continue to face significant challenges in solving real-world perception and recognition problems. These challenges include ensuring model generalization when dealing with noisy, imbalanced, or limited data; enhancing performance through self-supervised, few-shot, or transfer learning in cases of insufficient labeled data; integrating information across different scales, dimensions, and modalities. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Condición: new. Hardcover. The rapid advancement of deep learning technology has brought about transformative breakthroughs in perception and recognition systems across a wide range of applications. In addition to driving innovation in industrial sectors, it has opened up significant opportunities in fields such as intelligent transportation, smart cities, healthcare, and robotics.Deep learning significantly enhances the accuracy and robustness of perception and recognition systems through hierarchical feature extraction in multilayer neural networks, achieving remarkable results in areas such as soft sensing, image classification, natural language processing, and object detection. By training on large volumes of labeled data, deep learning algorithms are able to automatically learn complex feature representations and efficiently recognize objects during the perception process.As application scenarios grow more complex and data become increasingly diverse, deep learning models continue to face significant challenges in solving real-world perception and recognition problems. These challenges include ensuring model generalization when dealing with noisy, imbalanced, or limited data; enhancing performance through self-supervised, few-shot, or transfer learning in cases of insufficient labeled data; integrating information across different scales, dimensions, and modalities. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condición: New. Print on Demand.

Hardcover. Condición: new. Hardcover. The rapid advancement of deep learning technology has brought about transformative breakthroughs in perception and recognition systems across a wide range of applications. In addition to driving innovation in industrial sectors, it has opened up significant opportunities in fields such as intelligent transportation, smart cities, healthcare, and robotics.Deep learning significantly enhances the accuracy and robustness of perception and recognition systems through hierarchical feature extraction in multilayer neural networks, achieving remarkable results in areas such as soft sensing, image classification, natural language processing, and object detection. By training on large volumes of labeled data, deep learning algorithms are able to automatically learn complex feature representations and efficiently recognize objects during the perception process.As application scenarios grow more complex and data become increasingly diverse, deep learning models continue to face significant challenges in solving real-world perception and recognition problems. These challenges include ensuring model generalization when dealing with noisy, imbalanced, or limited data; enhancing performance through self-supervised, few-shot, or transfer learning in cases of insufficient labeled data; integrating information across different scales, dimensions, and modalities. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condición: New. PRINT ON DEMAND.

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.

Buch. Condición: Neu. Deep Learning for Perception and Recognition | Method and Applications | Buch | Englisch | 2026 | MDPI AG | EAN 9783725862665 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.