A Comprehensive Approach for Detecting and Classifying Loitering Events in Fishing Vessels Using Supervised and Semi-Supervised Learning-Reference-Cited by-同舟云学术

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A Comprehensive Approach for Detecting and Classifying Loitering Events in Fishing Vessels Using Supervised and Semi-Supervised Learning

Published:2023-08-25 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd Asian Conference on Innovation in Technology (ASIANCON)
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Author:

Sira Rishi Kumar¹,Tanjavur Irthiqua Moin¹,M S Guru Prasad.¹,Rajan Abraham²,Laxman ³,T G Mohan Kumar⁴

Affiliation:

1. Grapic Era (Deemed to be University),Dept. of Computer Science and Engg.,Dehradun,India

2. Nagarjuna College of Engineering and Technology,Dept. of Computer Science and Engg.,Bengaluru,India

3. School of Computing and Information Technology, REVA University,Bengaluru,India

4. Nitte Meenakshi Institute of Technology,Dept. of Information Science and Engg.,Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10269797/10269805/10269886.pdf?arnumber=10269886

Reference15 articles.

1. Brain Tumor Identification and Classification using a Novel Extraction Method based on Adapted Alexnet Architecture

2. Early Detection of Malignant Tumor in Lungs Using Feed-Forward Neural Network and K-Nearest Neighbor Classifier

3. An Improved Water Body Segmentation from Satellite Images using MSAA-Net

4. Stroke Disease Prediction based on ECG Signals using Deep Learning Techniques

5. A Novel Approach to Optimize the Performance of Hadoop Frameworks for Sentiment Analysis

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