Image segmentation review: Theoretical background and recent advances
Image segmentation is a significant topic in image refining and automated image analysis
with relevance for instance object recognition, diagnostic imaging scanning, mechanized …
with relevance for instance object recognition, diagnostic imaging scanning, mechanized …
Deep models for multi-view 3D object recognition: a review
This review paper focuses on the progress of deep learning-based methods for multi-view
3D object recognition. It covers the state-of-the-art techniques in this field, specifically those …
3D object recognition. It covers the state-of-the-art techniques in this field, specifically those …
Steel surface defect detection algorithm in complex background scenarios
BT Zhao, YR Chen, XF Jia, TB Ma - Measurement, 2024 - Elsevier
Detecting surface defects on steel poses a significant challenge attributed to factors such as
poor contrast, diverse defect types, complex background clutter, and noise interference …
poor contrast, diverse defect types, complex background clutter, and noise interference …
Transfer learning-based convolutional neural networks with heuristic optimization for hand gesture recognition
Human action recognition (HAR) has a considerable place in scientific studies. Additionally,
hand gesture recognition, which is a subcategory of HAR, plays an important role in …
hand gesture recognition, which is a subcategory of HAR, plays an important role in …
An efficient and improved scheme for handwritten digit recognition based on convolutional neural network
Character recognition from handwritten images has received greater attention in research
community of pattern recognition due to vast applications and ambiguity in learning …
community of pattern recognition due to vast applications and ambiguity in learning …
Deep6mAPred: A CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species
Abstract DNA N6-methyladenine (6mA) is a key DNA modification, which plays versatile
roles in the cellular processes, including regulation of gene expression, DNA repair, and …
roles in the cellular processes, including regulation of gene expression, DNA repair, and …
Prediction of engine combustion chamber outlet temperature field based on deep Learning: Application in aero-engine life extension control
Q Zheng, C Cai, H Zhang, H Zhang - Applied Thermal Engineering, 2024 - Elsevier
One of the current research hotspots is the prediction of combustion chamber flow field
based on deep learning methods, but how to effectively utilize these prediction results is a …
based on deep learning methods, but how to effectively utilize these prediction results is a …
Improving brain tumor classification: an approach integrating pre-trained CNN models and machine learning algorithms
Accurate detection of brain tumors is crucial for enhancing patient outcomes, yet the
interpretation of Magnetic Resonance Imaging (MRI) scans poses significant challenges …
interpretation of Magnetic Resonance Imaging (MRI) scans poses significant challenges …
[HTML][HTML] Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors
Abstract Convolutional Neural Networks (CNNs) play a crucial role in many image
recognition and classification tasks, recommender systems, brain-computer interfaces, etc …
recognition and classification tasks, recommender systems, brain-computer interfaces, etc …
Driver yawning detection based on long short term memory networks
W Zhang, J Su - 2017 IEEE Symposium Series on …, 2017 - ieeexplore.ieee.org
This paper proposes an efficient and nonintrusive approach for detecting Driver's Yawn
using a single camera based on Long Short Term Memory Networks. Fatigue is a significant …
using a single camera based on Long Short Term Memory Networks. Fatigue is a significant …