I will do medical image classification and detection in deep learning

Introducing our specialized service for the classification and diagnosis of medical images using deep learning techniques. At Cappeh, we focus on developing versatile systems for medical diagnosis, plant disease detection, and general object detection and classification across various domains such as healthcare and agriculture. Our team employs advanced deep learning methods, including neural networks, transfer learning, and multi-model architectures, to ensure accurate and timely results, particularly in real-time processing for swift decision-making. Our services encompass comprehensive data science tasks, from data preprocessing and augmentation to exploratory data analysis. Notable projects include brain tumor classification using transfer learning, real-time invasive species detection, and citrus leaf disease classification. For further details, feel free to reach out to us!

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$310

Published

7 days ago

Description

Introducing the service of classification and diagnosis of medical images in deep learning

Thank you for visiting our cappeh gig, where we specialize in developing versatile systems for medical diagnosis, plant disease detection, and general object detection and classification using images, videos, and real-time data. Our team leverages state-of-the-art deep learning techniques to provide accurate and timely results across various domains such as healthcare, agriculture, and more, with a focus on real-time processing for swift decision-making.

Our Services Include:

- Deep Learning:
- Neural Networks
- Transfer Learning
- Multi-model Neural Network
- TensorFlow
- Keras
- Image Processing
- Object Detection
- Image Classification
- Multi-class Classification
- Multi-label Classification

- Data Science:
- Data Preprocessing
- Data Augmentation
- Offline Augmentation
- Data Visualization
- Exploratory Data Analysis

Some of Our Projects:

- Real-time Invasive Species Plants Detection Based on CNN
- Brain Tumor Classification Using Transfer Learning Approach
- Plant Leaf Disease Classification Based on YOLOv9 Model
- Citrus Leaf Disease Classification Using One-Shot Object Detection
- Alzheimer's Disease Detection and Identification Using Deep CNNs