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Active Learning: Theory and Applications to Automatic Speech Recognition

Research paper #the-canvas { border: 1px solid black; direction: ltr; width: 100%; height: auto; } #paginator { text-align: center; margin-bottom: 10px; } Previous Next     Page: / window.onload = function () { var url = "https:\/\/bhavyagoel.github.io" + 'posts\/researchPDF\/rp-2.pdf'; var hidePaginator = ""; var pdfjsLib = window['pdfjs-dist/build/pdf']; pdfjsLib.GlobalWorkerOptions.workerSrc = "https:\/\/bhavyagoel.github.io" + '/js/pdf-js/build/pdf.worker.js'; var pdfDoc = null, pageNum = 1, pageRendering = false, pageNumPending = null, scale = 3, canvas = document.

July 14, 2021 Read

Semi Supervised Joint Learning for Hand Gesture Recognition

Features This is for Static Gestures Hand Gesture and Hand Pose Recognition Semi-Supervised learning scheme used to solve the problem of lacking proper annotation 3-D Hand Pose with foreground hand, and hand gesture Unconstrained environment dataset – Hand Posture: Only classify in classes – Hand Posture: positions of finger joints, view point, rotation, scale and so on. Semi-Supervised Scheme Knowledge Transfer: Transfer annotation by extracting shared features from hand gesture to hand pose and vice versa.

July 14, 2021 Read