Fish Disease Image Recognition Model

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@koolvishruth

Hi,I am from Banglore. With over 8 years of experience and expertise in software development, machine learning, data mining, and deep learning, I am confident that I can exceed your expectations for this fish disease image recognition model project. My significant skills in Python, as well as TensorFlow and PyTorch, align perfectly with your requirements for dataset cleaning, selecting suitable CNN/architecture, training the model to achieve 92% F1 score and of course re-creating final weights from raw images.

@AZTURK1

Hi there, I understand you need a production-ready image classification model to detect multiple fish diseases from high-resolution farm photos and I’m confident I can deliver a robust, deployable solution that meets your 92% F1 target. - Clean and augment the ~20 GB JPG/PNG dataset (class balancing, quality checks, smart augmentations) - Design/select a CNN/transformer (TensorFlow or PyTorch) and train with GPU-optimized pipelines; hyperparameter tuning until F1 ≥ 92% - Deliver trained model files, reproducible training scripts, Docker inference image, and evaluation report (precision, recall, confusion matrices) - Provide hand-off: short call and concise retraining guide; optional lightweight monitoring suggestions Skills: ✅ Image Recognition ✅ Python, TensorFlow/PyTorch ✅ Data Augmentation & Data Mining ✅ Deployment: Docker image / inference instructions ✅ Model reliability: evaluation, class balancing, performance tuning Certificates: ✅ Microsoft® Certified: MCSA | MCSE | MCT ✅ cPanel® & WHM Certified CWSA-2 I can start immediately and deliver the full package within the agreed 15 days. Could you share a sample of class distribution (number of images per disease/healthy class) and whether you already have any metadata (angles, timestamps, or camera types)? Best regards,

@growwithgdp

✅ I’ll build a high-accuracy fish disease detection model using **PyTorch (EfficientNet/ViT)** with data cleaning, augmentation, and fine-tuning to achieve 92%+ F1 score. ✅ Deliver reproducible training pipeline, evaluation report (precision/recall/confusion matrix), and optimized inference (CPU/GPU, Docker-ready). ✅ Clear documentation + handover for deployment and future retraining.

@sinchana0123

Hello, I can develop a high-accuracy fish disease classification model using PyTorch with transfer learning (e.g., EfficientNet/ResNet). I will handle dataset cleaning, augmentation, training, and fine-tuning to target ≥92% F1 on your held-out test set. Deliverables include reproducible training scripts, trained model files (CPU/GPU ready), full evaluation metrics (precision, recall, F1, confusion matrix), and a Dockerized inference setup. I can also provide a simple API for backend integration if needed. Ready to review the dataset and start immediately.

@ssldevmaster

Hi, I can easily DO your work IN 24 HOURS, DM me now to get started, PRICE NEGOTIABLE 100% Work satisfaction is provided

@jagrutib34

Hi, I have built a similar high-accuracy computer vision system for metal piece defect detection in industrial environments, where the model needed to identify surface cracks and anomalies in real-time with high precision. I’m an expert in OpenCV, deep learning model optimization, and production-grade deployment pipelines. Your aquaculture disease detection system is exactly the kind of structured, high-impact computer vision project I specialize in.

@rohank987

Hello, I’m excited to help you build a high-performance fish disease recognition system for real-time aquaculture monitoring. With strong experience in computer vision using TensorFlow and PyTorch, I’ve developed image classification models for medical and precision-detection use cases where accuracy and reliability were critical. My approach will begin with thorough dataset cleaning, class balancing, and augmentation to improve robustness and prevent overfitting. I will evaluate suitable architectures such as EfficientNet, ResNet, or Vision Transformers based on dataset size and complexity, selecting the model that offers the best trade-off between speed and accuracy. Through structured training, validation, and hyperparameter tuning, I will optimize the system to meet or exceed your 92% F1 score requirement on the held-out test set. Deliverables will include: • Production-ready trained model files (GPU and CPU compatible) • Reproducible Python training scripts from raw images • Detailed evaluation report with precision, recall, F1, and confusion matrix per class • Docker image or notebook for inference • Documentation or hand-off session explaining deployment and retraining If needed, I can also assist with backend integration to support your real-time monitoring pipeline. I focus on building scalable, maintainable solutions—not just hitting metrics, but ensuring long-term usability and performance. Ready to discuss your dataset and deployment goals.

@PyMLExpert1

Leveraging my extensive experience in Python and Deep Learning, I am confident in my abilities to deliver an exceptional solution to your fish disease image recognition challenge. I understand the critical nature of this task for the aquaculture industry and the need for utmost accuracy. Drawing from my repertoire of designing complex algorithms, I’m skilled at data cleaning, augmentation, model selection, training, validation, fine-tuning, and script packaging. I recognize that precision is vital in this project and I am committed to achieving high accuracies on each disease class. My aim is to create a model that meets or even surpasses your 92% F1 requirement. Furthermore, my proficiency in TensorFlow and PyTorch ensures I can develop a model that leverages the most suitable architecture for your dataset. As a bonus, I can also integrate this model with your back end system if desired. From experience in similar projects which involved detecting objects or medical conditions from images, I’m familiar with evaluating models using precision, recall and confusion matrices. I assure you that in addition to the trained model files and Python scripts you requested over GPU or CPU inference, you'll receive a comprehensive evaluation report. Finally, I offer a clear hand-off call or document to walk you through usage and possible future retraining steps for easy maintenance of the system.

@SubhashV013

i have worked on pedestrain detection in an crowded image using resnet50 mask R-CNN which highly segement objects with accurate image training which is similar to your proposal , first i give me dataset and i try to create model basing on accuracy you can decide whether to pay or not.

@anujs087

I can develop a Fish Disease Recognition model using deep learning techniques such as CNN with TensorFlow/Keras or PyTorch. The model will be trained on labeled fish images to accurately detect and classify diseases. I will handle data preprocessing, model training, testing, accuracy evaluation, and provide a complete working solution with documentation. I ensure clean code, good accuracy, and timely delivery within 7 days.

@tarekhemdan

I'm a professor at the Department of Computer Science in Faculty of Science, Minia University, where I'm specializes in research areas such as Artificial Intelligence, Computer and Society, and Data Mining. With vast expertise in Pattern Recognition, Classification, Machine Learning, Image Processing, Computer Vision, Feature Extraction, Signal, Image and Video Processing, Feature Selection, Pattern Classification, Object Recognition, Image Segmentation, Data Mining and Knowledge Discovery, Image Data Analysis, Video Processing, Digital Image Processing, Image Analysis, Face Recognition, Face Detection, Segmentation, Image Recognition, Knowledge Discovery, Semantic Web, Web Mining, Information Technology, Information Extraction, Websites, Web of Data, Advanced Machine Learning, Supervised Learning, Machine Vision, and other related fields, I'm currently engaged in a project that utilizes Machine Learning algorithms to predict optimal drug combinations.

@neerajmangal730

Leveraging my extensive experience in Python and Deep Learning, I am confident in my abilities to deliver an exceptional solution to your fish disease image recognition challenge. I understand the critical nature of this task for the aquaculture industry and the need for utmost accuracy. Drawing from my repertoire of designing complex algorithms, I'm skilled at data cleaning, augmentation, model selection, training, validation, fine- tuning, and script packaging. I recognize that precision is vital in this project and I am committed to achieving high accuracies on each disease class. My aim is to create a model that meets or even surpasses your 92% F1 requirement. Furthermore, my proficiency in TensorFlow and PyTorch ensures I can develop a model that leverages the most suitable architecture for your dataset. As a bonus, I can also integrate this model with your back end system if desired. From experience in similar projects which involved detecting objects or medical conditions from images, I'm familiar with evaluating models using precision, recall and confusion matrices. I assure you that in addition to the trained model files and Python scripts you requested over GPU or CPU inference, you'll receive a comprehensive evaluation report. Finally, I offer a clear hand-off call or document to walk you through usage and possible future retraining steps for easy maintenance of model.