Hyperspectral Imaging (HSI) has been extensively utilized in many real-life applications because it benefits from the detailed spectral information contained in each pixel. Notably, the complex characteristics i.e., the nonlinear relation among the captured spectral information and the corresponding object of HSI data make accurate classification challenging for traditional methods. In the last few years, Deep Learning (DL) has been substantiated as a powerful feature extractor that effectively addresses the nonlinear problems that appeared in a number of computer vision tasks. This prompts the deployment of DL for HSI classification (HSIC) which revealed good performance. This survey enlists a systematic overview of DL for HSIC and compared state-of-the-art strategies of the said topic. Primarily, we will encapsulate the main challenges of traditional machine learning for HSIC and then we will acquaint the superiority of DL to address these problems. This survey breakdown the stateof-the-art DL frameworks into spectral-features, spatial-features, and together spatial-spectral features to systematically analyze the achievements (future research directions as well) of these frameworks for HSIC. Moreover, we will consider the fact that

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Aim: To compare effectiveness of neurodynamics with and without wrist splint in patients with carpal tunnel syndrome.Study design: Randomized controlled trial. Settings: Farooq Hospital & Akhtar Saeed Trust teaching hospital,Lahore. Methodology: In present study 34 patients were randomly allocated into two groups in which each group contains 17 patients. Group A received combined treatment approach of neurodynamics and wrist splint while group B received only neurodynamics for two weeks .Improvement in functions and pain were recorded after 2 weeks .Initially baseline measurements were taken on DASH questioner and VAS. Present RCT study was carried out at Akhtar Saeed Trust Hospital,Lahore. Analysis was established through SPSS. Results: Independent sample t test was applied in present study of 34 patients as the mean difference was greater in group A in which combined treatment approach of wrist splint and neurodynamics were applied as compared to other group B in which only neurodynamics were applied.The p value is < 0.05 which shows results were significant. Results were more significant and superior in group A as compared to group B. Conclusion: Group A in which neurodynamics and wrist splint were used found to be more effective as compared to group B in which only neurodynamics were used. Keywords: Carpal tunnel syndrome; neurodynamics; wrist splint.