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Deniable Authentication Encryption for Privacy Protection using Blockchain
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Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications
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Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
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QoS-aware Virtual Machine (VM) for Optimal Resource Utilization and Energy Conservation
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Probabilistic Neural Network based Managing Algorithm for Building Automation System
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Fusion based Feature Extraction Analysis of ECG Signal Interpretation - A Systematic Approach
Volume-3 | Issue-1
Multi-scale CNN Approach for Accurate Detection of Underwater Static Fish Image
Volume-3 | Issue-3
Real Time Anomaly Detection Techniques Using PySpark Frame Work
Volume-2 | Issue-1
Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3
Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4
Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3
Audio Tagging Using CNN Based Audio Neural Networks for Massive Data Processing
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Frontiers of AI beyond 2030: Novel Perspectives
Volume-4 | Issue-4
Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
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Early Stage Detection of Crack in Glasses by Hybrid CNN Transformation Approach
Volume-3 | Issue-4
ARTIFICIAL INTELLIGENCE APPLICATION IN SMART WAREHOUSING ENVIRONMENT FOR AUTOMATED LOGISTICS
Volume-1 | Issue-2
Deep Convolution Neural Network Model for Credit-Card Fraud Detection and Alert
Volume-3 | Issue-2
Volume - 3 | Issue - 3 | september 2021
Published
30 August, 2021
Recently, the identification and naming of fish species in underwater imagery processing has been in high demand. This is an essential activity for everyone, from biologists to scientists to fisherman. Humans' interests have recently expanded from the earth to the sky and the sea. Robots could be utilized to send mankind to explore the ocean and outer space, as well as for some dangerous professions that human beings are unlikely to perform. Humans have recently shifted their focus from land-based exploration to celestial exploration and the sea. Robots are used for the activities that pose a risk to mankind, like exploration of the seas and outer space. This research article provides a solution to underwater image detection techniques by using an appended transmission map, refinement method and deep learning approach. The features are deeply extracted by multi-scale CNN for attaining higher accuracy in detecting fish features from the input images with the help of segmentation process. Object recognition errors are minimized and it has been compared with other traditional processes. The overall performance metrics graph has been plotted for the proposed algorithm in the results and discussion section.
KeywordsMachine learning Object detection
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