11 Result(s)
within
Chapter
Anuradha Chug
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Chapter and Conference Paper
Identifying Multiple Diseases on a Single Citrus Leaf Using Deep Learning Techniques
Deep learning techniques for classifying images into multiple classes have made significant strides in the past few years. Nevertheless, allocating multiple classes to a single image, as seen in object detecti...
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Chapter and Conference Paper
TLDC: Tomato Leaf Disease Classification Using Deep Learning and Image Segmentation
Deep learning (DL) has made significant progress in identifying and classifying plant diseases. The convolutional neural network (CNN) model was utilized to classify diseased and healthy tomato plant leaves fo...
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Chapter and Conference Paper
A Forecasting Technique for Powdery Mildew Disease Prediction in Tomato Plants
In the current scenario, plant disease detection is seeking attention from many agricultural scientists. Plant diseases are deeply influenced by the weather conditions, and each disease has its individual weat...
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Chapter and Conference Paper
Classification and Activation Map Visualization of Banana Diseases Using Deep Learning Models
Machine learning, especially deep learning (DL), comprises a modern, recent technique to process the images and data, with promising outcomes and enormous potential. DL is acquiring prevalence as it proves its...
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Chapter
Breast Cancer Prediction Using Nature Inspired Algorithm
Medical industry, though various researches over decades, has figured out breast cancer to be one of the most common diseases in women. Studies have shown that every eighth woman is suffering from it. This res...
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Chapter and Conference Paper
Deep Learning Models for Crop Quality and Diseases Detection
Deep Learning is acquiring momentum in the agricultural field for crop disease detection using image processing due to its computational power. Several deep learning techniques have been implemented in differe...
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Chapter and Conference Paper
Improving Software Maintainability Prediction Using Hyperparameter Tuning of Baseline Machine Learning Algorithms
Software maintainability is a prime trait of software, measured as the ease with which new code lines can be added, obsolete ones can be deleted, and those having errors can be corrected. The significance of s...
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Chapter and Conference Paper
Impact of Hyperparameter Tuning on Deep Learning Based Estimation of Disease Severity in Grape Plant
Accurate and quantitative estimation of disease severity in plants is a complex task, even for experienced agronomists and plant pathologists, where incorrect evaluation might lead to the inappropriate use of ...
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Chapter
Recent Advancements in Multimedia Big Data Computing for IoT Applications in Precision Agriculture: Opportunities, Issues, and Challenges
This chapter aims to present a survey on the existing techniques and architectures of Multimedia Big Data (MMBD) computing for Internet of Things (IoT) applications in Precision Agriculture, along with the opp...
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Chapter and Conference Paper
Recent Advancements in Image-Based Prediction Models for Diagnosis of Plant Diseases
India plays a significant role in the world as a major contributor to the overall food industry. Farming being a major occupation, crop protection from plant diseases has become a serious concern. The occurren...
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Chapter and Conference Paper
A Metric Suite for Predicting Software Maintainability in Data Intensive Applications
Software maintainability is the vital aspect of software quality and defined as the ease with which modifications can be made once the software is delivered. Tracking the maintenance behaviour of a software pr...
