Titlebook: Intelligent Systems Technologies and Applications 2016; Juan Manuel Corchado Rodriguez,Sushmita Mitra,El-S Conference proceedings 2016 Spr

誰在削木頭

Leaf Recognition Algorithm for Retrieving Medicinal Informationwith medicinal science and technology, India as a country has lost its track in the field of Ayurveda. Researchers and medicinal practitioners today, in spite of knowing that allopathic medicines are made using certain plant extracts, are oblivious about the medicinal the properties of plants. This

colony

EXPEL

Heuristic Approach for Face Recognition using Artificial Bee Colony Optimizationdeveloped algorithm in Swarm Intelligence (SI) that outperforms many of the established and widely used algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) under SI. ABC is being applied in diverse areas to improve performance. Many hybrids of ABC have evolved over the years

割讓

gusher

Blink Analysis using Eye gaze trackerperforming various tasks. The experimental suite for this analysis is based on the eye gaze coordinate data obtained from commercial eye gaze tracker. The raw data is processed through a FSM(Finite State Machine) modeled to detect the opening and closing state of an eye. The blink rate of a person v

尊敬

有幫助

Enhancement of Dental Digital X-Ray Images based On the Image Qualityment using methods like Histogram Equalization(HE), Gamma Correction(GC),and Log Transform(LT). The decision of the enhancement parameters and the method used is chosen, with the help of the image statistics (like mean, variance, and standard deviation). This proposed system also ranks the algorithm

Exhilarate

MRI/CT IMAGE FUSION USING GABOR TEXTURE FEATURESl fused image. To this the fused residual image obtained by combining the residue of the two images can be added to increase the information content. This approach was tested on MRI and CT images considering both mono-modal and multi-modal cases and the results are promising.

Meander

因無茶而冷淡

Recognition of Handwritten Benzene Structure with Support Vector Machine and Logistic Regression a C shows that both classifiers have accuracy of more than 97%. The result analysis shows that classification technique based on SVM classification performs better than classification technique using logistic regression.