In recent years, more and more deep learning frameworks are being applied to hyperspectral image classification tasks and have achieved great results. However, the existing network models have higher model complexity and require more time consumption. Traditional hyperspectral image classification methods te...
To obtain more reliable land cover information than traditional hard classification, spectral unmixing methods have been developed to estimate the composition of the mixed pixels, in terms of the proportions of land cover classes. The existing spectral unmixing methods usually require pure spectra (i....
A flow chart of the calculation to determine the hemoglobin amount is shown in FIG. 19. If a picture image is represented by a two-dimensional array IM(X,Y), X will signify the size of the picture image in the X direction and Y will signify the size of the picture image in the Y ...
A machine learning based methodology, using the extracted plant trait indicators for simultaneous stress severity level classification of drought, nitrogen and weed stress, released as part of the open source software suite [2]. With this methodology, we show that with spatio-temporal spectral data ...
Using the optimal cutoff values (Radscore40keV, − 0.008; RadscorePEI, 0.651) determined from the training cohort based on the maximum Youden index, the test cohort underwent dichotomous classification. Substantial differences in Radscore40keV and RadscorePEI were observed between early-stage and ...
– synthesis and verification of models; – improving the quality of the model and the choice of the most reliable models – solution in the most reliable model of diagnostic tasks (classification, recognition, identification), decision support and research of the modeled subject area by studying ...
image pre-processing and classification algorithms along with reference plant trait measurements and stress type and severity level labels to serve as ground truth. Our generic, plant agnostic pipeline starts with raw input imagery from RGB, stereo infrared (IR) and multispectral cameras, followed by...
5636Accesses 52Citations 4Altmetric Metrics Abstract Near infrared spectroscopy (NIRS) has been successfully used for non-invasive diagnosis of diseases and abnormalities where water spectral patterns are found to play an important role. The present study investigates water absorbance patterns indicative of...
FIG. 4 is a flow chart depicting an audio encoding process (400) performed by the extended band coder (350) of FIG. 3 to encode the extended band spectral coefficients. In this audio encoding process (400), the extended band coder (350) divides the extended band spectral coefficients into...
Purpose: To propose a classification of retinal astrocytic hamartoma based on spectral domain optical coherence tomography and correlate each class with systemic manifestations of tuberous sclerosis complex. Methods: Retrospective chart review conducted at four international referral medical retina centers. ...