Results 51 to 60 of about 28,970 (210)

An Attention‐Assisted Machine Learning System for Deep Microorganism Image Classification

Advanced Intelligent Systems, EarlyView.
An attention‐assisted DenseNet201 framework was developed for the classification of eight microorganism classes from microscopic images. The proposed model improved classification performance and achieved an accuracy of 87.38%. Advances in microbiology and environmental health fundamentally depend on precise and timely microorganism identification ...
Yujie Li, Ailing Gao, Guoxu Liu, Chunlei Chen, Yonghui Zhang, Sunkyoung Kang, M. Khosravi   +6 more
wiley   +1 more source

Regularizing Deep Networks by Modeling and Predicting Label Structure

, 2018
We construct custom regularization functions for use in supervised training of deep neural networks. Our technique is applicable when the ground-truth labels themselves exhibit internal structure; we derive a regularizer by learning an autoencoder over ...
Maire, Michael, Mostajabi, Mohammadreza, Shakhnarovich, Gregory   +2 more
core   +1 more source

Explainable AI‐Driven Optimization of Electrode Activation Reduces Power Consumption While Preserving Object Recognition in Retinal Prostheses

Advanced Intelligent Systems, EarlyView.
Explainable artificial intelligence (XAI) guides selective electrode activation in retinal prostheses by emphasizing visually informative regions. XAI‐assisted phosphene generation maintains object recognition performance while significantly reducing stimulation power.
Sein Kim, Hamin Shim, Maesoon Im
wiley   +1 more source

Improving Accuracy in Deep Learning-Based Mushroom Image Classification through Optimal Use of Classification Techniques

JOIV: International Journal on Informatics Visualization
The primary purpose of this research is to address the existing knowledge gap surrounding various lesser-known types of edible mushrooms. A common understanding exists that mushrooms are edible and possess numerous health benefits.
Johan Muliadi Kerta, Abdul Haris Rangkuti, Sian Lun Lau, Albert Kurniawan, Melanie Gabriela, Alicia Tandianto   +5 more
doaj   +1 more source

Video Time: Properties, Encoders and Evaluation [PDF]

, 2018
Time-aware encoding of frame sequences in a video is a fundamental problem in video understanding. While many attempted to model time in videos, an explicit study on quantifying video time is missing.
Gavves, Efstratios, Ghodrati, Amir, Snoek, Cees G. M.   +2 more
core   +1 more source

Ensemble Deep Learning–Based Wind Power Forecasting With Self‐Adaptive Osprey Optimization Algorithm

Energy Science &Engineering, EarlyView.
Design of Self‐Adaptive Osprey (SAO) algorithm: The novel SAO algorithm is designed by integrating the exploration capability of the conventional Osprey algorithm by including the self‐adaptiveness for enhancing the convergence rate. Ensemble Deep Learning for wind power forecasting: The wind forecasting is employed using the proposed Ensemble learning
Johncy Bai Johnson, Sivarani Thankamony Saradha Devi, Kumar Chandrasekaran, Sourav Barua   +3 more
wiley   +1 more source

Diabetic Retinopathy Severity Level Detection Using Convolution Neural Network

Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer
Diabetic retinopathy is a common complication of diabetes mellitus, leading to damage and blockage of retinal blood vessels. Early and accurate detection of diabetic retinopathy severity levels is crucial for timely treatment and prevention of blindness.
Achmad Dinofaldi Firmansyah, Saliyah Binti Kahar, Zilvanhisna Emka Fitri   +2 more
doaj   +1 more source

Wheat Stripe Rust Grading by Deep Learning With Attention Mechanism and Images From Mobile Devices

Frontiers in Plant Science, 2020
Wheat stripe rust is one of the main wheat diseases worldwide, which has significantly adverse effects on wheat yield and quality, posing serious threats on food security.
Zhiwen Mi, Zhiwen Mi, Zhiwen Mi, Xudong Zhang, Xudong Zhang, Xudong Zhang, Jinya Su, Dejun Han, Baofeng Su, Baofeng Su, Baofeng Su   +10 more
doaj   +1 more source

Identifying Venous Insufficiency in Head and Neck Reconstruction Flaps Using Machine Learning and Deep Learning Methods

Head &Neck, EarlyView.
ABSTRACT Background Venous insufficiency is a major cause of flap failure in head and neck reconstruction. AI provides a reliable, convenient solution for early detection. Methods Clinical data and postoperative flap photos of head and neck cancer patients (2018–2024) at our center were retrospectively collected, categorized into normal and venous ...
Yurong He, Jugao Fang, Lizhen Hou, Zufei Li, Shizhi He, Yanming Zhao, Qijia Li, Rongjia Li, Xiaoyu Shi, Jiayi Yang, Qi Zhong   +10 more
wiley   +1 more source

Densely Connected Neural Networks for Nonlinear Regression

Entropy, 2022
Densely connected convolutional networks (DenseNet) behave well in image processing. However, for regression tasks, convolutional DenseNet may lose essential information from independent input features.
Chao Jiang, Canchen Jiang, Dongwei Chen, Fei Hu   +3 more
doaj   +1 more source