Results 291 to 300 of about 324,009 (309)

A Novel Approach for Handwriting Recognition in Malayalam Manuscripts using Contour Detection and Convolutional Neural Nets

International Conference on Advances in Computing, Communications and Informatics, 2018
Neural Networks is a hot area of research for various kind of pattern recognition. Hand writing recognition is a domain coming under the field of pattern recognition which had captured a high research interest during the last 10 years.
Dhanya Sudarsan, Shelbi Joseph
semanticscholar   +1 more source

Bilingual Word Embeddings for Cross-Lingual Personality Recognition Using Convolutional Neural Nets

Interspeech, 2017
We propose a multilingual personality classifier that uses text data from social media and Youtube Vlog transcriptions, and maps them into Big Five personality traits using a Convolutional Neural Network (CNN).
Farhad Bin Siddique, Pascale Fung
semanticscholar   +1 more source

W–net: A Convolutional Neural Network for Retinal Vessel Segmentation

2021
In this paper we propose a method for retinal vessel segmentation based on a multi-stage deep convolutional neural network with short connections. The proposed method is a two-stage application of an improved U–net architecture. In the first stage, a probability score for the vascular structure presence is computed from a set of random patches taken ...
Mariano Rivera, Alan Reyes-Figueroa
openaire   +2 more sources

Elasto-Net: An HDL Conversion Framework For Convolutional Neural Networks

2018 52nd Asilomar Conference on Signals, Systems, and Computers, 2018
Hardware solutions for Convolutional Neural Networks (CNN) have emerged in the recent wake of their success in image classification. Although CNNs are effective in classifying images, they can be highly complex to implement in hardware. CNNs come in many shapes and sizes.
Tokunbo Ogunfunmi, Anaam Ansari
openaire   +2 more sources

S-Net: A Lightweight Convolutional Neural Network for N-Dimensional Signals

2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2018
Two dimensional Convolutional Neural Networks (Con-vNets) have been widely adopted as powerful models and have achieved state-of-the-art performance in many image related tasks. However, their extensions are still struggling for leading performance for high dimensional (HD) signal processing, partially due to the explosion of training parameters ...
Wenbin Yin, Yingxuan Cui, Yunhui Shi, Xiaoyan Sun   +3 more
openaire   +2 more sources

CIASM-Net: A Novel Convolutional Neural Network for Dehazing Image

2020 5th International Conference on Computer and Communication Systems (ICCCS), 2020
When light propagates in the medium such as haze, the image information collected by the imaging sensor is seriously degraded due to the scattering of particles, which greatly limits the application value of the image. In this paper, a novel convolutional neural network model called CIASM-Net is proposed to implement image dehazing.
Wen Qian, Chao Zhou, Dengyin Zhang
openaire   +2 more sources

AMI-Net: Convolution Neural Networks With Affine Moment Invariants

IEEE Signal Processing Letters, 2018
Affine moment invariant (AMI) is a kind of hand-crafted image feature, which is invariant to affine transformations. This property is precisely what the standard convolution neural network (CNN) is difficult to achieve. In this letter, we present a kind of network architecture to introduce AMI into CNN, which is called AMI-Net.
You Hao, Qi Li, Hanlin Mo, He Zhang, Hua Li   +4 more
openaire   +2 more sources

U-Net Based Convolutional Neural Network for Skeleton Extraction

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019
Skeletonization is a process aimed to extract a line-like object shape representation, skeleton, which is of great interest for optical character recognition, shape-based object matching, recognition, biomedical image analysis, etc.. Existing methods for skeleton extraction are typically based on topological, morphological or distance transform and are
Oleg Panichev, Alona Voloshyna
openaire   +2 more sources

Optical Flow Estimation with Convolutional Neural Nets

Pattern Recognition and Image Analysis, 2021
Syed Tafseer, Haider Shah, Xuezhi Xiang, Waqas Ahmed   +3 more
semanticscholar   +1 more source

Convolutional Neural Network U-Net for Trypanosoma cruzi Segmentation

2020
Chagas disease is a mortal silent illness caused by the parasite Trypanosoma cruzi that affects many people worldwide. A blood test is one of the preferred methods to get an accurate diagnosis of the disease but takes a long time and requires too much effort from the experts to analyze blood samples in the search of the parasites presence.
Allan Ojeda-Pat, Anabel Martin-Gonzalez, Roger Soberanis-Mukul   +2 more
openaire   +2 more sources