Deep Learning for Perception and Recognition (Hardcover)
Language: English
Published by Mdpi AG, 2026
- Hardcover
- New

Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
US$ 117.28
Quantity: 1 available
Add to basketItem description from seller
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.…
Seller Inventory # 9783725862665
- Title
- Deep Learning for Perception and Recognition (Hardcover)
- Author
- Gaochang Wu
- Publisher
- Mdpi AG
- Publication year
- 2026
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3725862664
- ISBN 13
- 9783725862665
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.
"Synopsis" may belong to another edition of this title.
CitiRetail
Stevenage, United Kingdom
AbeBooks seller since June 29, 2022
Shipping rates from United Kingdom to U.S.A.
| Item | 7 to 14 business days | 7 to 60 business days |
|---|---|---|
| First item | US$ 49.87 | US$ 49.87 |
Payment methods
Store description
Online business
Seller's business information
ABC BOOKS LIMITED
10 John Street
London, United Kingdom WC1N 2EB
Terms of sale
Orders can be returned within 30 days of receipt.
Shipping terms
Please note that titles are dispatched from our US, Canadian or Australian warehouses. Delivery times specified in shipping terms. Orders ship within 2 business days. Delivery to your door then takes 7-14 days.