In this study, we investigate this hypothesis in the context of major depressive disorder (MDD) and post-traumatic stress disorder detection (PTSD).
The automatic recognition of pathological speech, particularly from children with any articulatory impairment, is a challenging task due to various reasons.
For the automatic recognition of code-switching speech, the conventional approaches often employ an LID system for detecting the languages present within an utterance.
End-to-end (E2E) systems are fast replacing the conventional systems in the domain of automatic speech recognition.
The existing works mostly assume that the block structure is known a priori while learning the dictionary.
In this work, we have presented a novel method for detection of retinal image features, the optic disc and the fovea, from colour fundus photographs of dilated eyes for Computer-aided Diagnosis(CAD) system.
In the context of Computer Aided Diagnosis system for diabetic retinopathy, we present a novel method for detection of exudates and their classification for disease severity prediction.