Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy, bìa mềm
Deep learning has achieved impressive results in
image classification, computer vision, and natural language processing.
To achieve better performance, deeper and wider networks have been
designed, which increase the demand for computational resources. The
number of floating-point operations (FLOPs) has increased dramatically
with larger networks, and this has become an obstacle for convolutional
neural networks (CNNs) being developed for mobile and embedded devices.
In this context, Binary Neural Networks: Algorithms, Architectures, and
Applications will focus on CNN compression and acceleration, which are
important for the research community. We will describe numerous methods,
including parameter quantization, network pruning, low-rank
decomposition, and knowledge distillation. More recently, to reduce
(from binary to low-bit) the burden of handcrafted architecture design,
neural architecture search (NAS) has been used to automatically build
neural networks by searching over a vast architecture space. Our book
will also introduce NAS and binary NAS and its superiority and
state-of-the-art performance in various applications, such as image
classification and object detection. We also describe extensive
applications of compressed deep models on image classification, speech
recognition, object detection, and tracking. These topics can help
researchers better understand the usefulness and the potential of
network compression on practical applications. Moreover, interested
readers should have basic knowledge of machine learning and deep
learning to better understand the methods described in this book. Key
Features • Reviews recent advances in CNN compression and acceleration •
Elaborates recent advances on binary neural network (BNN) technologies •
Introduces applications of BNN in image classification, speech
recognition, object detection, and more
Thể loại:Computers - Algorithms and Data Structures
Năm:2024
Ngôn ngữ:english
Trang: 218
