BIOENGINEER

Enhancing BNN storage and performance requirements via efficient quantization and variable encoding

Binary neural networks have long promised to bring deep learning to the smallest and most power-hungry devices on the planet.
BIOENGINEER

Turning Loan Data Into Images Helps AI Predict Peer-to-Peer Credit Defaults

Researchers converted millions of LendingClub loan records into structure-aware grayscale images and showed that a hybrid ...
blog.csdn

TPAMI2017 | SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

说明 1）所述均基于如下环境：ECU-TEST 8.0、Win10系统、NI Veristand 2018（HIL测试）。不排除因为版本及软件环境问题，所述方法不奏效或有更好的方法，欢迎交流，一起提高。 2）本博客以问答形式 ...
Scientific Research Publishing

Badrinarayanan, V., Kendall, A. and Cipolla, R. (2017) SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation. IEEE Transactions on Pattern Analysis ...

ABSTRACT: The nearly analytic discretization of the frequency-domain wave equation produces large-scale, sparse, and ill-conditioned linear system, which challenge conventional iterative solvers. To ...
quantumzeitgeist

Quantum CNN & Vision Transformer: 99.77% Accuracy

Image classification currently relies on powerful, yet classically constrained, computational methods, but researchers are now exploring quantum machine learning as a potential pathway to significant ...
science

Attention-based map encoding for learning generalized legged locomotion

Dynamic locomotion of legged robots is a critical yet challenging topic in expanding the operational range of mobile robots. It requires precise planning when possible footholds are sparse, robustness ...
IEEE

Supervised Convolutional Encoder-Decoder With Gated Linear Units for Detecting Fetal R-Peaks

Abstract: Noninvasive fetal electrocardiography (ECG) is prevalently used for monitoring fetal heartbeats during pregnancy due to its affordability, ease of use, and constant monitoring capability. A ...
Scientific Research Publishing

Chollampatt, S. and Ng, H.T. (2018) A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction. Proceedings of the AAAI Conference on Artificial ...

ABSTRACT: With the widespread use of Chinese globally, the number of Chinese learners has been increasing, leading to various grammatical errors among beginners. Additionally, as domestic efforts to ...
blog.csdn

【图像去噪】论文精读：Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections（REDNet）

起源： 2014年，Sutskever提出的简单Enc-Dec模型 paper：Sequence to Sequence Learning with Neural Network 解决sequence to sequence转换的问题，采用了编码和解码的结构 其中，编码是将source sequence转化为一个context ...
IEEE

Optimizing the Hyperparameters of Fully Convolutional Encoder–Decoder Networks for SAR Image Segmentation

Abstract: Fully convolutional encoder-decoder networks have been developed for the segmentation of sensing synthetic aperture radar (SAR) images. A recent one called the multiscaled attention U-net ...