Results 91 to 100 of about 297,664 (309)

MostafaNabieh/Convolutional-Neural-Network-CNN: CNN Project

, 2020
Cnn project by Tensorflow ...
Mostafa Nabieh, Mostafa Nabieh (8597619)
core   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Comparative Study: Flower Classification using Deep Learning, SMOTE and Fine-Tuning

Journal of Applied Informatics and Computing
Deep learning is a technology that can be used to classify flowers. In this research, flower type classification using the CNN method with several existing CNN architectures will be discussed.
Vincentius Praskatama, Guruh Fajar Shidik, Amanda Prawita Ningrum   +2 more
doaj   +1 more source

Table detection ANN model based on Faster R-CNN

, 2020
Table detection ANN model based on Faster R-CNN trained on three datasets ICDAR 2017, Marmot and ...
Andrey Mikhailov (8613789)
core   +1 more source

Recent Advances in Laser‐Induced Graphene‐Based Gas Sensors: From Sensing Mechanisms to Biomedical Applications

Advanced Science, EarlyView.
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas, Ankan Dutta, Shuvendu Das, Abu Musa Abdullah, Wanqing Zhang, Fatema Tuz Zohra, Huanyu Cheng   +6 more
wiley   +1 more source

Analysis of digital intelligent financial audit system based on improved BiLSTM neural network

Nonlinear Engineering
Traditional auditing methods have difficulties in detecting various financial issues hidden in massive amounts of data. With the continuous advancement of deep learning and digital technology, new audit methods have been provided for computer auditing ...
Zhu Xincai
doaj   +1 more source

EEG Depression Recognition Based on Multi-domain Features Combined with CBAM Model

Journal of Harbin University of Science and Technology
At present, the electroencephalogram (EEG) identification method for depression mainly uses a single feature extraction method, which cannot cover multi-domain feature information, resulting in poor classification performance of the existing model ...
CHEN Yu, HU Xiuxiu, WANG Sheng
doaj   +1 more source

Detection of corona faults in switchgear by ssing 1D-CNN, LSTM, and 1D-CNN-LSTM methods

, 2023
The damaging effects of corona faults have made them a major concern in metal-clad switchgear, requiring extreme caution during operation. Corona faults are also the primary cause of flashovers in medium-voltage metal-clad electrical equipment.
SK Tiong (17274427), CT Yaw (17274421), K Ali (9851552), YA Mohammed Alsumaidaee (18620206), AN Abdalla (18463605), SP Koh (17274424), AA Raj (18620209), CP Chen (16393815), Talal Yusaf (11435077)   +8 more
core  

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Mesh R-CNN

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019
Rapid advances in 2D perception have led to systems that accurately detect objects in real-world images. However, these systems make predictions in 2D, ignoring the 3D structure of the world. Concurrently, advances in 3D shape prediction have mostly focused on synthetic benchmarks and isolated objects. We unify advances in these two areas. We propose a
Gkioxari, Georgia, Malik, Jitendra, Johnson, Justin   +2 more
openaire   +5 more sources