SANTANU BANERJEE’s Post

Hi. #connections! I am very glad to say our paper was published under the Journal Of Technology. In this paper, we introduce an innovative ideas towards the farmers. We have developed a comprehensive system for detecting plant diseases and recommending appropriate pesticides to safeguard crops from potential threats. Leveraging Convolutional Neural Network (CNN) classification techniques, our system not only identifies diseases but also assists in protecting crops from animals and other detrimental factors. By integrating advanced CNN algorithms, we ensure efficient and accurate detection of diseases, enabling farmers to take proactive measures to protect their crops. In our approach, we have targeted three key diseases affecting crops: bacterial blight, brown spot, and leaf smut, alongside a category for healthy plants. Each dataset contains 4000 images for both training and testing phases, ensuring robust model training and evaluation. Our system has achieved an impressive accuracy rate of 90%, indicating its reliability in disease detection and classification. This high level of accuracy is instrumental in providing farmers with reliable guidance on identifying crop diseases accurately. By accurately detecting these diseases, farmers can take timely and targeted actions to address them, thereby minimizing crop damage and optimizing yields. Keywords: Machine Learning, CNN Algorithm, Plant disease detection and Remedies Recommendation for Rice Crop. #Research Paper #journaloftechnology #cnn #riceplantdisease

🚀 Cocoa Disease Classification Project Complete! 🌱 I just wrapped up a project where I used YOLOv8 to classify cocoa diseases into four groups: mirid, black pod, frost pod, and healthy. The model achieved a mAP of 82.3%, and everything was handled efficiently without needing an extra classifier—YOLOv8 took care of it all. Though diagnosing these diseases at these late stages may not offer much help to the farmer in managing the crops, this project was still a great learning experience. It’s fascinating to see how computer vision can be applied in agriculture, even with its challenges. #ComputerVision#YOLOv8#AgricultureTech

Alhumdulilah! explained the methodology and concept of Agricultural Plant Diseases Identification - From Traditional Approach to Deep Learning as detailed in the article by Jameer Kotwal, Dr. Ramgopal Kashyap, and Dr. Shafi Pathan. Here is a glimpse of what the article contains👇😅 https://lnkd.in/dVJBywwS #DeepLearning #MachineLearning #PlantDiseaseDetection #AIinAgriculture

🌿 Task 3 Completed! 🌿 🚀 Excited to share my latest project on Leaf Disease Detection! 🌱 In this task, I've developed an image-based automatic inspection system to categorize plant leaves as healthy or infected using self-designed image processing and deep learning techniques. 🌱💻 This project aims to revolutionize agriculture by enabling early detection and management of plant diseases, ensuring healthier crops and better yields. 🌾 #DataScience #DeepLearning #ImageProcessing #Agriculture #MachineLearning #ArtificialIntelligence #CodeAlpha #LeafDiseaseDetection #CodeAlpha

A key question in investigating plants 🌾 is the plants' color. The color reports a lot on growth and development. It is particularly relevant for flowering 🌻 and fruiting 🥭. Colors indicate responses to stress 🟡 and diseases 🟤. Most prominently, the green 🟢 color of leaves is an important indicator of the plant's status. The green is caused by chlorophyll, and the greenness of leaves 🥬 relates to chlorophyll presence. Thus, greenness can be taken as an indicator for leaf health and quality. In image processing for plant phenotyping, color analysis and greenness determination are important steps to characterize plant phenotypic properties. In the LemnaTec Software Suite we provide tools for such analyses that can be applied to a broad range of species. For more information, please visit our website, contact us via info@lemnatec.com, or call +49 2408 981850. #phenotyping #imageprocessing #lemnatec #nynomic

I have successfully conducted research on Precision Agriculture, focusing on leveraging AgriTech to enhance agricultural efficiency and productivity. Specifically, I developed a real-time tomato plant disease classification system using pre-trained deep learning models. This system integrates a modified GoogleNet with a live camera feed, enabling accurate and timely disease detection and classification in the field. By empowering Nigerian farmers with this technology, they can identify tomato plant diseases at an early stage, enabling proactive measures like targeted treatment or crop isolation. This early intervention can significantly reduce crop losses and boost tomato yields in the region. #AI #MachineLearning #PrecisionAgriculture #ComputerEngineering #GraphicsAndVision

🚀 Thrilled to Share Our Latest Research Breakthrough!🚀 Our paper, “Optimized Crop Disease Identification in Bangladesh: A Deep Learning and SVM Hybrid Model for Rice, Potato, and Corn”, is now published in J. Imaging. This study presents a cutting-edge hybrid model using EfficientNetB0 for feature extraction and SVM for classification. We achieved **97.29% accuracy** in identifying diseases like late blight in potatoes, brown spot in rice, and common rust in corn. 🌾🍚🌽 The model significantly outperformed CNN, VGG16, ResNet50, and others, offering a valuable tool for bolstering food security in Bangladesh. Check out the full paper here: [https://lnkd.in/gtvfG4iq) #AIinAgriculture #DeepLearning #SVM #EfficientNetB0 #FoodSecurity #Bangladesh #CropHealth #ResearchBreakthrough

We often get asked about the impact of "dead DNA" in the soil on agronomic decisions. Tuesday Simmons, PhD explains the insights growers can glean from a comprehensive look at all the DNA in a soil sample. 🔗 https://bit.ly/3SgQqJV #SoilHealth #DNA #Data #Sustainability

🙋Hey network.. Shall we discuss about Crop genetics today..! Crop Genetics 🧬 Unlocking the potential of crops through genetics! Dive into the fascinating world of crop breeding and genetic engineering, where scientists are developing resilient varieties that can withstand pests, diseases, and climate extremes. 🌱 From hybridization and marker-assisted selection to gene editing techniques like CRISPR, there are endless possibilities for enhancing crop traits such as yield, nutritional content, and tolerance to environmental stress. 🌾 By harnessing the power of genetics, farmers can cultivate more productive and sustainable agricultural systems to feed a growing population. 🚜 Join the conversation and learn how innovation in crop genetics is shaping the future of farming! Image courtesy : Scitech Daily #CropGenetics #AgricultureScience #Innovation