ALEXNET FEATURE EXTRACTION AND MULTI-KERNEL LEARNING FOR OBJECTORIENTED CLASSIFICATION

13 citations as recorded by crossref.

1. Recognition Method of Massage Techniques Based on Attention Mechanism and Convolutional Long Short-Term Memory Neural Network S. Zhu et al. 10.3390/s22155632
2. Application of the artificial intelligence system based on graphics and vision in ethnic tourism of subtropical grasslands H. Yu 10.1016/j.heliyon.2024.e31442
3. OBJECT-BASED APPROACHES FOR LAND USE-LAND COVER CLASSIFICATION USING HIGH RESOLUTION QUICK BIRD SATELLITE IMAGERY (A CASE STUDY: KERBELA, IRAQ) H. Jaber et al. 10.3846/gac.2022.14453
4. Mirrored conditional random field model for object recognition in indoor environments H. Chen et al. 10.1016/j.ins.2020.11.006
5. A Postearthquake Multiple Scene Recognition Model Based on Classical SSD Method and Transfer Learning Z. Xu et al. 10.3390/ijgi9040238
6. A PLSTM, AlexNet and ESNN Based Ensemble Learning Model for Detecting Electricity Theft in Smart Grids N. Javaid 10.1109/ACCESS.2021.3134754
7. Spartan Face Mask Detection and Facial Recognition System Z. Song et al. 10.3390/healthcare10010087
8. Change Detection Techniques for Land Cover Change Analysis Using Spatial Datasets: a Review S. Kumar & S. Arya 10.1007/s41976-021-00056-z
9. Geospatial Land Use and Land Cover Changes Detection over the Last 40 Years with Validation by Ground Truthing Using an Integrated Approach of Remote Sensing and Geographic Information Systems in the Amman Zarqa Basin, Jordan A. Mohammad & T. Odeh 10.14246/irspsd.12.3_161
10. Efficient Dynamic Reconfigurable CNN Accelerator for Edge Intelligence Computing on FPGA K. Shi et al. 10.3390/info14030194
11. Image classification on Post-Earthquake damage assessment: A case of the 2023 Kahramanmaraş earthquake G. Özerol Özman et al. 10.1016/j.jestch.2024.101780
12. Analysis of the proficiency of fully connected neural networks in the process of classifying digital images. Benchmark of different classification algorithms on high-level image features from convolutional layers J. Janke et al. 10.1016/j.eswa.2019.05.058
13. Design of Deep Convolution Neural Networks for categorical signature classification of raw panchromatic satellite images G. Rohith & L. Kumar 10.1007/s11042-022-12928-7