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In the agricultural sector, plant leaf diseases and harmful insects represent a major challenge. Faster and more reliable prediction of leaf diseases in crops may help develop an early treatment technique while reducing economic losses considerably. Current technological advances in deep learning have made it possible for researchers to improve the performance and accuracy of object detection and recognition systems significantly. In this chapter, using images of plant leaves, the authors introduced a deep-learning method with different datasets for detecting leaf diseases in different plants and concerned with a novel approach to plant disease recognition model, based on the classification of the leaf image, by the use of deep convolutional networks. Ultimately, the approach of developing deep learning methods on increasingly large and accessible to the public image datasets provides a viable path towards massive global diagnosis of smartphone-assisted crop disease.

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Number plate recognition brings a drastic improvement for the city traffic enhancement. It provides the direction in which the steps should be taken for working of an effective intelligent transportation system. ANPR have become necessity for traffic control management due to rapid increment of vehicles. The main aim of ANPR is to monitor traffic and for security purpose. Recognition of number plate uses image processing techniques and latest technology in detecting characters on vehicle license plates automatically. In recent years, there are many technological developments in recognizing license plate area of research. Image processing protocols like OCR technology allow the traffic surveillance to deal with several problems that occurs in criminal investigation, toll collection, monitoring traffic, controlling speed, parking management etc. For efficient management of traffic and mass surveillance in transportation system, an ANPR system is essential. With the aid of image processing algorithms and vehicle images dataset, it becomes possible to monitor traffic at a large scale. Vehicle images are helpful for recognizing characters on license plates by performing image segmentation, feature extraction and character recognition. Data collected through captured images are utilized in the commercial applications, law enforcement, traffic applications etc. The software examines the vehicle picture as an input image that results in displaying the plate numbers. The system with image processing used reliably for traffic detection where modification of the technologies enables an accurate acknowledgement of vehicle number plates. There are several ANPR systems developed, working on character recognition of LP by the help of image processing technique. This paper reviews the performance by researchers in this particular area towards meeting goals of transportation system. It also provides major issues and challenges in this field.