Titlebook: Nature Inspired Optimization Techniques for Image Processing Applications; Jude Hemanth,Valentina Emilia Balas Book 2019 Springer Nature S

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Nature Inspired Optimization Techniques for Image Processing Applications

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Firefly Optimization Based Improved Fuzzy Clustering for CT/MR Image Segmentation,ts having a natural capacity to illumine in dark with glowing and flickering lights and firefly optimization algorithm was modeled based on its biological traits. The preprocessing stage comprises of artifacts removal and denoising by Nonlinear Tensor Diffusion (NLTD) filter. The computation time wa

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Plant Phenotyping Through Image Analysis Using Nature Inspired Optimization Techniques,nt efficiently. Due to its simplicity, robustness and flexibility, Swarm intelligence acts as a backbone for extracting the phenotyping properties of the plants in designing computer vision systems which can help to raise the food production.

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Cuckoo Optimization Algorithm (COA) for Image Processing,lassified into two portions: cuckoos and eggs. The cuckoo societies then start to change their environment to better one and start reproducing and putting eggs. Such endeavor of Cuckoos to enhance their life’s environment is the Cuckoo Optimization Algorithm. In this chapter, a comprehensive discuss

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Analyzing the Effect of Optimization Strategies in Deep Convolutional Neural Network,h Adam optimizer constantly minimizes the objective function compared with other standard optimizers such as momentum, Rmsprop, and Adadelta. Dropout and batch normalization techniques are adapted to improve the model performance further by avoiding overfitting. Dropout function deactivates the insi