Automatic Number plate detection for law enforcement using optical recognition system

Automatic Number Plate Recognition (ANPR) is a specialized type of Optical Character Recognition System (OCR). It is a method of reading a vehicle's license plate using OCR to create vehicle registry or location data. ANPR is utilized by a variety of agencies around the world to enforce the law, including determining whether a vehicle is registered or not. Government entities, such as highways agencies, can categorize traffic movements for computerized toll collection. Images of the text from the license plate can be stored and processed using the ANPR system. Infrared cameras are often employed to take photographs in any lighting condition, whether it is day or night. To be more accurate ANPR technology should also consider plate variations from place to place.

Crop Recommendation Using Machine Learning

The population of India is over one billion. Nearly 65 percent of the population of India lives in villages with the main occupation being agriculture. The diverse climatic conditions in the country result in the production of a large number of agricultural items. Many surveys have proved that the suicide rate of farmers is proliferating over years due to the selection of the wrong crop resulting in less yield. In some areas, farmers lack information about the composition of soil and weather conditions and may choose the wrong crop to sow which results in lesser yield. Production of crops depends on geographical parameters like humidity, rainfall and properties of soil such as pH, and NPK content. Integration of technology with agriculture helps the farmer to improve his production. The main goal of agricultural planning is to achieve the maximum yield rate of crops by using a limited number of land resources. This paper mainly focuses on recommending the appropriate crop using ML Algorithms ( Decision Tree, Naive Bayes, Random Forest ) based on soil composition and weather conditions to maximize the yield of the farm and increase the economic condition of India’s farmers.

Weather Forecasting for Batu Pahat Using Neural Network

Nowadays, weather forecasting plays a vital role in human activities. The complexity of data gathering in the meteorology department and high technical costs lead to inaccurate weather forecasting. Due to minimizing this problem, an application of using an artificial neural network (ANN) has been developed to forecast weather conditions using the Matlab compiler. This application will help users to define the weather conditions daily well and made early preparation to encounter uncertainty. This application performs in Multilayer Perceptron (MLP) using the back-propagation (BP) algorithm. The data is undergoing training and testing based on actual data obtained from the Malaysian Meteorological Department. The result will show in graph plotting for the training and testing process. Predictive accuracy for each step of stimulation will measure using Mean Square Error (MSE) graph in this application. Therefore, this application will be able to assist the Malaysian Meteorological Department to forecast weather, so our government and people have sufficient time to prepare and solve.

A Personalized Recommender System

Due to social media, e-commerce, and the broader digitization of businesses, a data surge has occurred during the previous decade. The information is used to make informed decisions, forecast market trends, and identify patterns in consumer preferences. Following the widespread adoption of internet services, recommendation systems have become commonplace. The idea is to use filtering algorithms to recommend products to users who might be interested in them. Users are given recommendations for a media item such as movies by discovering user profiles of people who share similar interests. The preferences of users are first determined by allowing them to rate movies of their choosing. After some time, the recommender system will be able to better understand the user and recommend films that are more likely to get higher ratings. It also considers the impact of personal and situational factors on the user experience. In comparison to previous models, the experimental findings on the TMDB dataset provide a dependable model that is precise and generates more customized movie recommendations.

A Hybrid Approach for Neural Network in Pattern Storage

Your mind does not manufacture mind. Your mind forms neural networks. Neural networks had been effectively carried out to numerous sample garage and type troubles in phrases in their mastering ability, excessive discrimination electricity, and exceptional generalization ability. The achievement of many mastering schemes isn't always assured, however, seeing that algorithms like backpropagation have many drawbacks like stepping into the nearby minima, for that reason imparting suboptimal solutions. In the case of classifying big sets and complicated patterns, the traditional neural networks are afflicted by numerous problems inclusive of the dedication of the shape and length of the network, the computational complexity, and so on. This paper introduces the neural computing techniques especially radial foundation features network. Various upgrades and trends made in an artificial neural network for rushing up training, keeping off neighborhood minima, growing the generalization capacity, and different capabilities are reviewed.