Results 41 to 50 of about 22,800 (222)
FPGA-Based Acceleration on Additive Manufacturing Defects Inspection
Sensors, 2021 Additive manufacturing (AM) has gained increasing attention over the past years due to its fast prototype, easier modification, and possibility for complex internal texture devices when compared to traditional manufacture processing.
Yawen Luo, Yuhua Chen
doaj +1 more source
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2022 A binarized neural network (BNN) accelerator based on a processing-in-memory (PIM)/ computing-in-memory (CIM) architecture using ultralow-voltage retention static random access memory (ULVR-SRAM) is proposed for the energy minimum-point (EMP) operation ...
Yusaku Shiotsu, Satoshi Sugahara
doaj +1 more source
, 2016 We introduce a method to train Binarized Neural Networks (BNNs) - neural networks with binary weights and activations at run-time and when computing the parameters' gradient at train-time. We conduct two sets of experiments, each based on a different framework, namely Torch7 and Theano, where we train BNNs on MNIST, CIFAR-10 and SVHN, and achieve ...
Hubara, Itay +2 more
openaire +2 more sources
Classification of Hull Blocks of Ships Using CNN with Multi-View Image Set from 3D CAD Data
Journal of Marine Science and Engineering, 2023 In order to proceed with shipbuilding scheduling involving hundreds of hull blocks of ships, it is important to mark the locations of the hull blocks with the correct block identification number.
Haemyung Chon, Daekyun Oh, Jackyou Noh
doaj +1 more source
Sensors, 2021 Recently, as technology has advanced, the use of in-vehicle infotainment systems has increased, providing many functions. However, if the driver’s attention is diverted to control these systems, it can cause a fatal accident, and thus human–vehicle ...
Seunghyun Oh +4 more
doaj +1 more source
Architecturing Binarized Neural Networks for Traffic Sign Recognition
, 2023 Traffic signs support road safety and managing the flow of traffic, hence are an integral part of any vision system for autonomous driving. While the use of deep learning is well-known in traffic signs classification due to the high accuracy results obtained using convolutional neural networks (CNNs) (state of the art is 99.46\%), little is known about
Postovan, Andreea, Eraşcu, Mădălina
openaire +2 more sources
Binarized Neural Networks for Resource-Efficient Spike Sorting
IEEE AccessDeep learning is fastly gaining ground in neuroscience. In the field of implantable brain computer interfaces, a fundamental application of deep learning is to sort action potentials (known as spikes), measured with extracellular electrodes, according to
Luca M. Meyer +2 more
doaj +1 more source
FP-BNN: Binarized neural network on FPGA [PDF]
Neurocomputing, 2018 Deep neural networks (DNNs) have attracted significant attention for their excellent accuracy especially in areas such as computer vision and artificial intelligence. To enhance their performance, technologies for their hardware acceleration are being studied.
Liang, Shuang +4 more
openaire +3 more sources
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)
, 2020 Deep neural networks (DNN) have shown remarkable success in a variety of machine learning applications. The capacity of these models (i.e., number of parameters), endows them with expressive power and allows them to reach the desired performance.
Becking, Daniel +3 more
core +1 more source
A Multi-Layer Holistic Approach for Cursive Text Recognition
Applied Sciences, 2022 Urdu is a widely spoken and narrated language in several South-Asian countries and communities worldwide. It is relatively hard to recognize Urdu text compared to other languages due to its cursive writing style.
Muhammad Umair +6 more
doaj +1 more source