Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
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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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Hybrid Parallel Image Processing Algorithm for Binary Images with Image Thinning Technique
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QoS-aware Virtual Machine (VM) for Optimal Resource Utilization and Energy Conservation
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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
Volume-3 | Issue-4
Frontiers of AI beyond 2030: Novel Perspectives
Volume-4 | Issue-4
Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4
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 - 5 | Issue - 2 | june 2023
Published
07 June, 2023
Diagnosis of fish disease in aquaculture is a necessary process and needs an exceptionally high level of competency to sustain hatchery and pond production systems. Developing an system to overcome the challenges faced by fish farmers in stopping the spreading the disease that leads to economic loss, is a crucial task. A crucial initial phase in preventing the spread of disease is early identification of diseases in fish. The fish disease usually propagates quickly through the water, affecting large numbers of fish and causing financial loss to the farmers. Since tilapia aquaculture is one of the methods for producing food that is expanding the quickest and has the highest export value, we’d like to know more about the fish disease that affects this sector. The research uses the pathogen-infected fish. System is developed by working perfect image processing and machine learning techniques together. The proposed work has two phase. Image pre-processing has been used in the first phase to, respectively, reduce distortion and magnify the image. In the second section, the system extracts the relevant information and uses machine learning approaches for recognising the diseases. A trained machine learning model has been deployed to the first fraction's processed images. Then, using the chosen fish image dataset to study the fish disease, the research integrates an extensive experiment combining different methods.
KeywordsFish Disease CNN VGG16 Aquaculture Diagnosis
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