Author: Haroon Khalil
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Generative adversarial networks
Novelty of generative adversarial networks (GAN) lies in technicality of its design. It is a type of unsupervised machine learning which includes computerized innovation such that to understand the similarities or prototype data in the manner that system produces the result. GANs are smart models to build a productive system by modelling a problem having…
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Recurrent neural network
Recurrent neural network (RNN) is a type of neural network where output of the previous loop is considered as input for the current loop. General applications of generative neural network are speech recognition, handwriting recognition, analysis of sequence of data etc. Also, generative neural network automatically generates programming codes that give a predefined objective. Working…
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Convolution neural networks
Convolution neural network (CNN) structure is based on feed forward neural network and it is designed on an animal cortex and uses multi-layered perceptron for this process. In CNN the minimum amount of pre-processing rectified linear unit activation functions are often used. General applications are image/video recognition, natural language processing, chess etc. Convolution is used…
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Deep learning
Deep learning is a modern method that has been successfully applied in various domains. Deep learning has various applications such as image processing and text classification. Since the successful rate of deep learning is very high in other domains, so it is applied to agriculture methods too. Deep learning covers several layers of neural networks…
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Forecasting of livestock
Farm animal production deals with the problem of production system. The foremost scope of machine learning applications in farm animal production is precise judgment of monetary balances with the help of which the producers can get information based on production line monitoring and thus can gain profits. This is because the machine learning algorithms have…
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Welfare of animals
The field of animal welfare takes care of the health and well-being of animals so as to maintain a balance in the ecosystem. The key application of machine learning is in monitoring animal behaviour during the early exposure of infection.
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Management of irrigation
Irrigation is an important part of agriculture. It plays a significant role in yield productivity. Irrigation should neither be in excess nor less but should be balanced. To maintain these conditions certain factors need to be considered which are soil type, land topography, weather, type of crop, water quality etc.
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Management of quality of crop
To increase the value of crop and reduce the wastage one has to classify quality of crop with minimum error. The penultimate sub-category for the crop is developed for the identification of characteristics associated with the crop class.
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Recognizing plant
In comparison with the conventional approach for classification of plant using comparison of shape and colour of leaves machine learning can give exact and faster results by analysing the leaf vein morphology which provides additional information about characteristics of leaf. The foremost objective is the automatic recognition and categorization of different plant varieties so as…
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Soil management
The soil management plays a key role in yield efficiency, ecological stability and human health both directly and indirectly. Soil is a diverse natural resource having complex processes and fuzzy mechanism in which the temperature of soil also plays an important role in the precise investigation of climatic variations of an area and its ecological…