Leaf Disease Classification using Deep Learning Models -- 2

@tadinhkien

Greetings, Thank you for considering my application for this project. As an AI Engineer and Developer with over 8+ years of experience, I bring a wealth of knowledge and expertise in the field of Python, Deep Learning. I have carefully reviewed the project description and am eager to discuss your specific needs and requirements in more detail. My commitment is to provide dedicated support and consistent follow-up throughout the project's lifecycle. Please feel free to reach out to me to further discuss how I can contribute to the success of your project. Looking forward to the opportunity of working together. Best regards, KuroKien

@nrajuu07

I am an experienced Machine Learning and Deep Learning expert with a strong background in computer vision, CNNs, SVM, and transfer learning. Your Leaf Disease Classification project aligns perfectly with my expertise, and I am confident in delivering a robust model that meets all your requirements.

@amirrmusavifr

Hi, I’m an AI expert with professional experience in computer vision, with a proven track record of working on complex image processing and AI/ML model development. With skill sets: • Algorithm Development: Strong understanding of computer vision algorithms and techniques, including convolutional neural networks (CNNs), object detection, image segmentation and feature extraction. • Model Training & fine-tuning: Develop and train machine learning models tailored for image analysis and visual data interpretation. I have worked on some well-known models like YOLO, RCNN, U-Net, Deeplab, ViT etc. • AI Integration: Implement and integrate AI models into existing software and hardware systems, ensuring high performance and scalability. • Data Analysis: Analyze and process large datasets of images and video feeds to identify patterns, trends, and insights. • Data Handling: Experience in handling and processing large datasets, including image and video data. Familiarity with data augmentation techniques and synthetic data generation. • Performance Optimization: Optimize algorithms and models for real-time processing and ensure they can handle large-scale data efficiently. • Programming Skills: Proficient in programming languages such as Python. Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras. • Tools & Libraries: Proficiency with OpenCV, scikit-image, and other relevant libraries. Experience with version control systems like Git.

@ashrafsbai6655

Hi there, I checked your requirements and guarantee you that i have relevant experience in Python,ml and data science it's gonna be done within the highest quality . Let's contact via chat so that I can start work immediately

@snbhanja

Hi, I have trained leaf disease classification models for different types including classes from tomato, apples etc. Recently did similar project using ViT models. I can do the same using three models you mentioned using keras and SVM, CNN etc. let’s connect. I will share full code with evaluation metrics, roc auc plots etc.

@SakibKaiser

Hello, With 5+ years in plant pathology AI, I’ve built models like a 98.2% accurate cassava disease classifier (12 classes) and a severity estimator (MAE: 3.8% area). I’ll address your project’s unique challenges—38-class classification + stage/severity detection—using a hybrid CNN approach. --- Workflow & Innovation 1. Multi-Task Learning Architecture - Backbone: Pretrained EfficientNet-B4 (optimal for leaf images). - Heads: - Disease Classification: 38-class output (softmax). - Health Stage: 4-stage classifier (Grad-CAM attention maps). - Severity: Regression head with % area affected (custom loss: Dice + MSE). 2. SVM Baselines - HOG+SVM: Sliding window HOG features (64x64 patches). - VGG16+SVM: Feature extraction from block5_pool. 3. Overfitting Mitigation - Data: MixUp augmentation, RandErasing. - Model: Label smoothing, Stochastic Depth. --- Deliverables - Code: Jupyter Notebook with: - All 3 models (SVM-HOG, SVM-VGG16, CNN). - Interactive Grad-CAM visualizations (severity heatmaps). - Report: Metrics (Accuracy, F1, per-class PR curves) + overfitting analysis (train vs val curves). - Models: .h5 (CNN), .pkl (SVMs). --- Let’s connect to finish this project in 3 days. Waiting for you message. Best, Shakib Kaiser

@saba106

I am an expert statistician, Research Writer, and data analyst with more than eight years of experience. I have full command of Excel analysis, SPSS, STATA, R LANGUAGE, AND PYTHON. I am an expert in creating time series prediction models, working with survey data, conducting marketing analysis, building estimators, and medical analysis. I am a perfect match for your project share other details of the work so I can start working on your project. Will complete task on time.

@imranahmadquresh

Hi, I understand you need Machine Learning Expert using Python for Leaf Disease Classification. I offer my services for this project. I have made many Machine Learning based projects using Python as follows; • Predict Johnson & Johnson data using ARIMA & LSTM. • Stock Price Prediction of Amazon data and bank data using ARIMA & LSTM. • Handwritten Digit Recognition using Fourier response & SVM polynomial. • Classification of CIFAR-10 using different NN models. • Classification of London Fire Brigade incidents 2019-2022 data using Decision Tree. • Vehicle Classification using PCA, k-NN, Logistic regression, Decision tree, random forest, NN & CNN. • IOT Attacks Prediction using SVM, Decision Tree & Random Forest. • Prediction extent of disease of ECG data using Random Forest & SVM. • Sign Language Recognition using SVM using min-max feature scaling, z-score method & PCA. • Classification of dementia disease using XGboost & Logistic Regression. • Classification of Iris & Breast cancer using SVM, Decision Tree, NN & Naive Bayes. • Classification of Muffin & Cupcake ingredient data using SVM. • Prediction of Solar Radiance using SVM & Bayesian Ridge. • Clustering fingerprint images using K-Means. • Data analysis of Wales Employment data using PCA, Correlation, K-means & Hierarchical Clustering. • Data analysis of Sensor data using multi-variate Linear Regression, Correlation, Normalization & Regularization. I ensure to complete your project efficiently and on time.

@hasanudoy

Hello, I have necessary data preprocessing knowledge and machine learning experience using python. I am very much familiar with python libraries like pandas, numpy, Scikit-learn, seaborn, scipy, tensor flow, keras, pytorch, matplotlib etc. I have done regression analysis, time series analysis, bio medical signal analysis, image processing, classification, segmentation, pose keypoints detecrion etc. Let's discuss about your projects on chat for more details.

@Senavirathna1014

I am theekshana, a designer by passion, an engineer by profession. Being an all-round artistic tech-savvy geek, I spend most of my time nourishing new design ideas and giving them a tangible shape. Playing around with IoT modules and creating some useful projects out of them is another niche of mine, which seems most congenial to me and which I relish doing a lot. and also I'm an expert Machine Learning Engineer & proficient in modeling and training the deep neural networks using python libraries. I will assist you in your (Non-Academic/Academic) IoT projects involving ESP8266, ESP32, Arduino, Raspberry Pi, and MQTT and Machine learning and image processing following tools Tools: Tensorflow Keras Pytorch My services include: Modeling the neural network Training the neural network Fine Tuning Transfer Learning IOT related hardware and software Applications: Spam Detection Chats Sentiment Analysis Hate Speech Detection Text Emotions Detection Image Classification Image Segmentation Object detection Object Tracking

@EngrAnasAwan5

I am excited to apply for your Leaf Disease Classification Model project. With expertise in deep learning, computer vision, and large-scale image classification, I will develop a high-accuracy model that can effectively classify plant leaf diseases and assess severity. Project Approach & Key Features ✅ Multi-Class Disease Classification ✅ Health Condition Assessment ✅ Leaf Area Analysis for Severity Detection ✅ Performance Optimization ✅ Evaluation & Metrics Models & Technology Stack ✔ CNN Model – Custom-built deep learning model with multiple convolutional layers. ✔ SVM + HOG – Feature extraction using Histogram of Oriented Gradients for SVM classification. ✔ SVM + VGG16 – Transfer learning approach using VGG16 features with SVM. ✔ Frameworks & Tools – TensorFlow, Keras, Jupyter Notebook for efficient development. Deliverables ✅ Well-structured and documented Python code. ✅ Training logs & visualization graphs (accuracy/loss trends). ✅ Final trained model files (.h5 or .pkl) for deployment. ✅ Comprehensive performance report with insights on overfitting/underfitting. With my expertise in AI-driven image classification, I am confident in delivering an optimized and scalable solution for your project. Let's connect to discuss further!

@ABDOKAMA

Hi, I Co-Founder a startup called SANABEL, specializing in disease detection and pest monitoring for plants. I can develop the Leaf Disease Classification Model for you, ensuring high accuracy. I also have access to additional datasets to enhance the project. If there are any issues with the project, you can receive a full refund. If you'd like to see examples of my previous work on leaf disease and pest detection, I’d be happy to share those with you. Let’s collaborate to achieve the best results!

@kaushalp71

Proposal for Leaf Disease Classification Model Development Dear Sir/Ma'am, I am excited to submit my proposal for developing the Leaf Disease Classification Model as per your requirements. With a strong background in Machine Learning, Deep Learning, and Computer Vision, I am confident in delivering a robust and efficient solution. About Me: I am currently pursuing a B.S. in Data Science from IIT Madras, with hands-on experience in machine learning, deep learning, and image classification. I have worked on various projects, including stock price prediction using LSTM, image classification using MobileNet, and AI-driven predictive modeling. My expertise lies in building end-to-end machine learning pipelines, optimizing model performance, and handling large datasets efficiently. I have strong proficiency in TensorFlow, Keras, OpenCV, and Scikit-learn, along with experience in transfer learning, SVM-based feature extraction, and CNN architectures. I am passionate about leveraging AI to solve real-world challenges and believe this project aligns perfectly with my skills. I am eager to contribute to this project and ensure a high-performing, well-documented solution. Looking forward to your response. Best regards, Kaushal

@yasranafees

Dear Client, I am an experienced Machine Learning and Deep Learning practitioner with expertise in image classification, CNNs, and Transfer Learning using TensorFlow and Keras. I can develop an efficient Leaf Disease Classification Model that accurately identifies plant diseases across 38 classes while analyzing severity. How I Will Approach This Project: ✅ Dataset Preparation & Augmentation – Ensuring quality input for robust training. ✅ Feature Extraction (HOG & VGG16) – Using SVM for initial classification. ✅ Deep Learning (CNNs & Transfer Learning) – Implementing multiple convolutional layers for better accuracy. ✅ Performance Evaluation – Calculating Accuracy, Precision, Recall, and F1 Score. ✅ Overfitting & Underfitting Handling – Using Dropout, Batch Normalization, and Regularization techniques. ✅ Model Deployment & Report Generation – Saving the final trained model (.h5/.pkl) and providing proper documentation. Timeline & Price: ? Bid Amount: ₹7,000 INR ⏳ Delivery Time: 7 Days ? Paid to You After Fee: ₹6,300 INR I am confident in delivering highly accurate results with proper documentation and performance visualizations. Looking forward to collaborating on this exciting project! Best regards, [Yasra Nafees]

@AmitKumar119

I am a data scientist. I have worked specially with computer vision. I can do this as you have described.

@omarfathy203

Dear Client, I am excited to apply for this project and bring my expertise in Machine Learning and Deep Learning to develop an accurate Leaf Disease Classification Model. With experience in CNNs, SVM, Transfer Learning, and AI model evaluation, I am confident in delivering a high-performing solution tailored to your dataset of 87,000 images across 38 classes. My Approach: Model Development: Implementing SVM with HOG and VGG16, as well as a custom CNN to extract rich feature representations. Classification & Severity Analysis: Ensuring precise disease stage detection and quantifying the affected leaf area. Performance Optimization: Addressing overfitting & underfitting, tuning hyperparameters, and providing a detailed analysis of Accuracy, Precision, Recall, and F1 Score. Technologies: Working with TensorFlow, Keras, OpenCV, and Jupyter Notebook to ensure efficient model training and testing. Deliverables: Well-documented Python code with structured workflows Model performance reports with graphs and key metrics Final trained model files (.h5/.pkl) for easy deployment With a strong background in Deep Learning, NLP, and AI model development, I am eager to contribute to this project. Looking forward to discussing further details and aligning on expectations. Best regards, Omar Fathy

@chankit13

m the best candidate for this project because of my strong background in AI and machine learning, particularly in the domain of plant disease classification. I have hands-on experience working on a multi-class classification project for tomato plant leaf diseases using CNNs, which involved data preprocessing, model development, and deployment. Additionally, I have prior experience in potato disease classification, where I successfully implemented deep learning techniques to identify and categorize different potato plant diseases.

@Muhammad92492

With over 5 years of experience in Machine Learning, Deep Learning, and Computer Vision, I have successfully developed numerous models similar to what your project demands. Utilizing TensorFlow and Keras as my primary tools, I've become skilled in training CNNs and handling extensive datasets like yours. In fact, I have previously implemented SVM with HOG and VGG16 for feature extraction, which aligns perfectly with your requirements. One particular area that sets me apart is my emphasis on handling overfitting and underfitting issues explicitly. By addressing them effectively throughout the model training process, I ensure the final product offers robust performance. This approach extends to using various evaluation metrics such as Accuracy, Precision, Recall, F1 Score, which go into your project design brief. Another strength I bring to the table is my commitment to well-documented code and analysis. You can expect not just a functional model but also thorough documentation explaining its working principles making it easy for you to use or update the model. With me onboard, your Leaf Disease Classification Project will receive meticulous attention at every stage ensuring accurate identification and classification of leaf diseases along with detailed severity assessment. So let's work together to make this happen!

@hinnaa

Hi, I am working on a similar plant disease detection project using the PlantVillage dataset (38 healthy and diseased plant classes) with various ML and DL models. I can meet your requirements using SWM and VGG16 in TensorFlow or PyTorch. Feel free to message me to see related work and discuss further. Thank you!